ancori - 2000 - the economics of knowledge

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The Economics of Knowledge: The Debate

about Codification and Tacit KnowledgeBE R N A R D AN C O R I a , A N T O I N E B U R E T H b and P AT R I C K

CO H E N D E T c

(aIRIST/GERSULP-BETA, Université Louis Pasteur, Strasbourg BETA,bUniversité Louis Pasteur, Strasbourg–LIO, Université de Haute Alsace,

Mulhouse BETA and cUniversité Louis Pasteur, Strasbourg, France. Emails:[email protected], [email protected] and

[email protected])

The aim of this paper is to shed some light on the complex relationships between codified and tacit knowledge. This supposes a first step is to distinguish clearly the notion of knowledge from the notion of information. A model of knowledge as a structure is then proposed from which an analysis of the content, significance and implications of the tacit dimension of knowledge can be derived. The paper emphasizes the importance of the context, the modes of conversion of knowledge and the role of knowing communities when analysing the relationships between tacit and codified knowledge.

1. IntroductionWhile the current literature in economics agrees on the large and rapidlygrowing importance of knowledge, 1 either as an input or as an output of theeconomic system, there are strong controversies about the ways to representknowledge. An important debate is related to the analytical status of tacitknowledge.

To be treated as an economic good, knowledge must be put in a form that

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1 The belief of the increasing importance of knowledge for society is shared by many authors (e.g.Dasgupta and David, 1994; Gibbons et al., 1994; Callon and Foray, 1997; Lundvall, 1988). The convictionof the increasing importance of knowledge is echoed in other related disciplines. For example, Drucker(1993) argued that knowledge is the only meaningful resource today. For Toffler (1990), the battle for the

control of knowledge (‘the ultimate replacement of all other resources’) and the means of communicationis heating up all over the world. Reich (1991) contends that the only true competitive advantage will resideamong those who are equipped with the knowledge to identify, solve and broker new problems. Theincreasing importance of knowledge even modifies how society perceives the historical dimension: Castells(1998) shows by analyzing the diffusion of the micro-informatics that the invention of the microprocessorhas impacted on the economic context, including the labor conditions and the time scale.

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allows it to circulate and be exchanged. The main transformation investigatedby economists is the transformation of knowledge into information, i.e. thecodification of knowledge. It is through this form that economists generally

measure and assess knowledge objectively (or at least ‘comfortably’). Theprocess of codification allows them to treat knowledge-reduced-to-informa-tion according to the standard tools of economics. 2 ‘Information is knowledgereduced to messages that can be transmitted to decision agents. We can takethe standard information-theoretic view that such messages have informationcontent when receipt of them causes some action’ (Dasgupta and David,1994). This approach makes it incumbent that knowledge becomes an objectwith discernible and measurable characteristics. Although it is just the

tangible sign of the tremendous increase of all forms of knowledgeproduction, the rapid cumulative expansion of the codified knowledge-baseof society is frequently presented as a key characteristic of the developmentof modern economies and has contributed to the legitimation of the approachwhereby the analysis of knowledge is restricted to its codified form. Eco-nomics has thus traditionally taken the view that there is hardly meaningfuldistinction between information and knowledge. This theoretical positiondates back to the approach suggested by some prominent economists,such as Hayek (1945), 3 Nelson (1959) 4 and Arrow (1962). These authors

2 It seems that this is what Simon (1999) had in mind when he wrote: ‘All the aspects of knowledge—itscreation, its storage, its retrieval, its treatment as property, its role in the functioning of societies andorganization—can be (and have been) analyzed with the tools of economics. Knowledge has a price and acost of production; there are markets for knowledge, with their supply and demand curves, and marginalrates of substitution between one form of knowledge and another.’ However, the message brought forwardby Simon is somewhat ambiguous, for he continues his statement by arguing: ‘Knowledge is simply oneamong many commodities in which our economy trades, albeit one of large and rapidly growingimportance. It requires special treatment because of its special properties.’ One of the main concerns of thepresent contribution is precisely to determine these special properties.

3 Hayek conceived the problem of knowledge for society in such a way that at a given moment in timeeach individual holds some knowledge and that there is a need to ‘mobilize’ socially all these forms of dispersed knowledge. He drew attention to the importance of implicit, context-specific knowledge(knowledge of the particular circumstances of time and place) compared with the knowledge of generalrules (what he called scientific knowledge): ‘The peculiar character of the problems of a rational economicorder is determined precisely by the fact that the knowledge of the circumstances we must make use of never exists in concentrated or integrated form, but solely as the dispersed bits of incomplete andfrequently contradictory knowledge which all the separate individuals possess. The economic problem of society is thus not merely a problem of how to allocate given resources . . . it is a problem of the utilizationof knowledge not given to anyone in its totality’ (Hayek, 1945). For Hayek, the solution to this problemresides in the price mechanism to communicate information through the market process through whichindividual knowledge is mobilized socially. Hayek raised an important issue which is the way knowledgeis efficiently shared and exchanged through interaction between agents, but considered the solution interms of the allocation of information provided by the price-information signals. Nevertheless, the questionleft open is that the coordination of agents holding their own stock of knowledge independently is notsufficient to achieve economic ends, especially when knowledge itself is the object of action.

4 Nelson (1959) and Arrow (1962) focused on the ‘production’ of new knowledge, whether in thetechnological domain or in the scientific one. They essentially examined the characteristics of knowledge-reduced-to-information as a public good. For Arrow, the process of invention is interpreted

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clearly emphasize some key characteristics of knowledge for economics, anddeliberately focus on the fact that knowledge can be reduced to information.They certainly do not consider the possibility that knowledge is information,

but many of the economists that they inspired did.This view and the related hypothesis on the properties of knowledge

(transferability, rivalry and appropriability) are challenged among others byevolutionary economists (Dosi and Marengo, 1994; Pavitt, 1997) andsociologists of scientific knowledge (Callon et al., 1999). They highlight theimportance of the learning processes by which knowledge is producedand underline its contextual features. Even the most codified knowledge—scientific knowledge—cannot systematically be transferred (Collins, 1985).

As Callon (1999) points out, scientific knowledge is not diffused; it isreplicated with high costs, because what is replicates are the structures of research (such as laboratories and instruments) and not the results themselves.In other words, the knowing how (the tacit knowledge) cannot be dissociatedfrom the knowing about (the codified knowledge).

Schematically, two extreme positions are conflicting: on the one handthere is the ‘absolutist position on codification’ for which all knowledge canbe codified. According to this position, there could be some tacit knowledge

as an economic residual of knowledge, but this tacit knowledge could be(at some cost) codified. Codified knowledge is thus considered as a puresubstitute for tacit knowledge. On the other hand, there is the ‘absolutistposition on tacit knowledge’ for which all forms of codified knowledge requiretacit knowledge to be useful. Codified and tacit knowledge are thus viewedas essentially complementary. The aim of this contribution is to investigatea ‘reasonable position’ on the use of knowledge in economics, by trying toshed light on some of the complex relationships between codified and tacit

knowledge. We are interested in the process of transformation of knowledgeinto a commodity—which can be called the ‘commodification’ of knowledge.At the same time, with respect with the codification process, we also want toemphasize the following lines of arguments.

First, codification should not be assimilated to commodification. Even if codification is an important vector for commodification, there are cases whereknowledge may be commodified without being codified. Knowledge may

broadly as the production of knowledge which can be assimilated to information. He raised the problemof appropriability by showing that it is difficult or even impossible to create a market for knowledge onceit is produced. It is therefore difficult for producers of knowledge-reduced-to-information to appropriatethe benefits that flow from it. ‘There is a fundamental paradox in the determination of demand forinformation; its value for the purchaser is not known until he has the information, but then he has in effectacquired it without cost’ (Arrow, 1962). Again, the complexity of knowledge is clearly reduced to aninformation-codified form. It is as much remarkable as this contribution has inspired public interventionin the domain of R&D for decades.


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be commodified as a service such as in after-sales explanation services thataccompany the buying of complex goods (computers, for instance). One canfind numerous cases where in fact knowledge is commodified on markets in

both codified and tacit forms; for instance, in most countries driving schoolsoffer two kinds of ‘knowledge products’: they make sure that drivers will‘know the codes’ (the pure codified form) and they train them through prac-tice and experience acquisition (in a purely tacit form). On the other hand,knowledge may be codified without becoming a commodity, as in a case of internal operating procedures within a given organization, that are of no valuefor other organizations.

The second reason for which the process of codification should be

considered carefully is the risk of completely assimilating knowledge andinformation. In this paper we will insist on the need to clearly distinguishknowledge from information. There is a need to achieve better understandingof the mechanisms operating ‘ behind the scene’ of codification. We especiallystress the cognitive and organizational mechanisms mobilized by the codi-fication process. Indeed, if economists do not consider these mechanisms (thatare usually studied by other disciplines such as psychology), there is a risk of misinterpreting some key aspects of codification of knowledge. For instance,

certification processes aim at extracting and converting tacit knowledge intoa codified form; but in order to be used, the latter form mobilizes againforms of tacit knowledge. It underlines that the relation between codified andtacit knowledge is not just a question of complementarity, nor a question of substitutability: beyond the transformation of knowledge as an object, thecodification process also raises the question of the capacity of the knower toexploit different categories of knowledge.

Furthermore, the distinction between codified and tacit knowledge is not

the only complex dimension of the process of transformation of knowledge.Another crucial aspect to be considered is the transformation that takesplace between individual and collective knowledge. The formation and use of knowledge depend on the nature of the organizations and other collectivesets. Considering knowledge as resulting from a social process raises con-siderable issues, in particular the need to understand how knowledge canbe transmitted from the level of the organization to an individual, andreciprocally. As many authors have shown (Nonaka and Takeuchi, 1995), this

transmission requires different conversion mechanisms (tacit to codified,codified to tacit, etc.) to operate within a given organization and betweendifferent organizations. They clearly emphasized that the individual/collectivedimension strongly interferes with the tacit/codified dimension. 5

5 The fact that the tacit/codified and the individual/collective are the two main dimensions that drive


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In order to clarify the process of transformation of knowledge, the paperis constructed along the following steps: secton 2 distinguishes the notionof knowledge from the notion of information, and more precisely, points out

that knowledge is not a mere stock resulting from the accumulation of aninformation flux. We thus emphasize that knowledge is closely dependent onthe cognitive abilities of the actors who hold it, and that it cannot beseparated from the communication process through which it is exchanged. Insection 3, we propose the building of a structure of knowledge resultingfrom complementary layers (crude knowledge, knowledge of how to useknowledge, knowledge of how to transmit knowledge and knowledge of howto manage knowledge). This representation reinforces the understanding of

the distinction between knowledge and information, and helps to underlinethe cognitive and strategic implications of the transformation of knowledge.Section 4 investigates the content, the significance and the implications of the tacit dimension of knowledge. Section 5 explores the conditions and theconsequences of the transformation of knowledge from the individual to thecollective level (and reciprocally). As a conclusion, section 6 draws lessonsfrom the above discussions and proposes some new avenues of research.

2. In Search of a Useful Distinction between Information and Knowledge in Economics

The growing interest in knowledge in the current economic literature and theincreasing questioning of the assimilation of knowledge to information lead usto investigate first some of the main epistemic considerations of knowledge,in order to specify the economic meaning of it. It is certainly not the point

here to try to solve the theoretical debates of other disciplines, but ratherto acknowledge that each economic theory relies on a given epistemologicalvision of knowledge. It is well known that the classical approach of economicsadopts a vision of knowledge in line with the rationalistic school in epi-stemology. This vision allows the reduction of knowledge to information,or more precisely allows knowledge to be considered a stock accumulatedfrom interaction with an information flux. We suggest in this contribution anapproach to knowledge in economics close to constructivism, 6 and suggest

the transformation of knowledge is materialized for instance in the different typologies of knowledge thathave been proposed by economists. Most of them refer to these two dimensions. See Annex 1.

6 In a constructivist approach, a behaviour, an action or a message has no objective reality: it only existsin the subjective perception of actors belonging to the same social system. The actors’ cognitive structuresand their cognitive abilities to recognize, to interpret or to ignore facts become central in the way theyorganize their representation of the world [for a review of the use of the constructivist paradigm, seeWhittington (1993)] (see Lemoigne, 1990).


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relaxing some of the classical hypotheses regarding the building of knowledgethat help to make room for introducing the tacit dimension of knowledge andthe problem of the collective building of knowledge onto the economic scene.

2.1 The Linear Model

The traditional school in economics relies on rationalism as the cognitiveapproach to knowledge. Rationalism assumes the existence of an a prioriknowable external reality which is true at all times and in all places and whichis the highest grade of knowledge. Such knowledge does not need to be

justified by any sensory experience.7

Absolute truth is deduced from rationalreasoning grounded in axioms (which can be assimilated to a ‘quest for thetruth’). Thus knowledge can be attained deductively by employing mentalconstructs such as concepts, laws and theories. This classical definition of knowledge as ‘justified true belief’ supposes a split between the knower andthe known. 8

The traditional rationalistic process of the quest for knowledge can bedescribed by a linear process of transformation [that Winkin (1996) called the‘telegraphic’ communication, with reference to Shannon’s model]: data areturned into information, information into knowledge, and finally knowledgeis confronted with ‘wisdom’ (or ‘meta-knowledge’ that encompasses beliefsand judgements). This vision of the transformation emphasizes the role of information-processing as a critical step in the formation of knowledge for agiven cognitive entity. It also presumes that a linear process is involved inincreasing the complexity of the search for knowledge, where the first step

7 Conversely, empiricism argues that there is no a priori knowledge and that the only source of knowledge is the sensory experience. Everything in the world has an intrinsically objective existence. Onlyexperience (sensation, reflection) can provide the mind with ideas. Knowledge of the world is to be foundin the investigation of an empirical reality and not through rational introspection. That is the reason whysuch tools as language and logic are shaped to be used for the analysis of empirical reality. By linguisticanalysis, it is possible to derive the meaning of concepts that are empirically verifiable. One’s personalknowledge is supposed in such a vision to correspond to reality.

8 In the classical rationalistic vision of knowledge, there is no connection between knowledge and action.What is at stake is a spectator theory of knowledge that separates theory and practice. To a large extent,the traditional vision of economics is based on such a position which tends to accept the separation of economic knowledge from the economic subject. If one relaxes this classical separation, then there is roomfor introducing explicitly the role and importance of learning processes related to experience in the domainthat is considered. For instance, the role of learning processes has been emphasized by James (1950) whendealing with pragmatism. He proposed to consider the building of knowledge as an interactive relationshipbetween ‘knowledge about’ (‘wissen’ in German, ‘savoir’ in French) and ‘knowledge of acquaintance’(‘kennen’ in German, ‘connaître’ in French). Action though experience provides immediate knowledge of ‘acquaintance’, while knowledge ‘about’ is the result of systematic thought that eliminates the subjectiveand contextual contingencies. This distinction has an implication in terms of social and organizationaldimensions: knowledge of ‘acquaintance’ needs essentially to be gathered and integrated, while knowledge‘about’ needs essentially to be diffused.


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consists in transforming ‘data’ (considered as ‘raw material’ from nature) intostructured pieces of information that are then, in a second step, channelledinto the search for knowledge. Each piece of information brings with it a

‘quantum of novelty’ (according to Shannon’s theory) that contributes toincreasing the stock of knowledge and the combinatorial complexity of thisknowledge stock. To a large extent this representation coincides with the con-ceptualization of information as a flux that builds a stock of knowledge andthat serves as a foundation for a justified set of beliefs. 9

This elementary vision of the relationship between knowledge andinformation carries some important implications:

1. The quantitative measure of information as a ‘quantum’ that circulatesthroughout the process raises the question of efficiency of the informationprocessing system. The more efficient the channels of treatment of dataand information, the more information can circulate and the more ef-ficient the process of formation of knowledge can become because of theability to examine and assess different combinations of quanta. (Of course,such a statement requires careful examination, in particular when takinginto account the question of the existence and role of ‘noise’ in the trans-

mission of information or in the examination and assessment process.)2. This representation supposes—at least implicitly—that knowledge will

result from the codification and classification of information. Thus, thequality and the accuracy of the formation of knowledge depends directlyon the features of this treatment of information.

To a large extent, most of the economic uses of the concept of knowledge arebased on such a paradigm. However, a growing number of voices now argue

that this vision is too simplistic and are calling for a change of paradigm. Oneof the most significant contributions that tried to go beyond this restrictedversion of the relationship between information and knowledge is Machlup(1983). To outline his meaning, Machlup quoted the famous extract fromBoulding (1953):

We cannot regard knowledge as simply the accumulation of informationin a stockpile, even though all the messages that are received by the brain

may leave some sort of deposit here. Knowledge must itself be regardedas a structure, a very complex and quite loose pattern with its parts con-nected in various ways by ties of varying degrees of strength. Messages are

9 The last step of the process, the way wisdom (beliefs and judgements) considers knowledge, dependson questions of methods such as falsification in the Popperian point of view.


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continually shot into this structure; some of them pass right throughits interstices without effecting any perceptible change in it. Sometimesmessages ‘stick’ to the structure and become part of it . . . Occasionally,however, a message which is inconsistent with the basic pattern of themental structure, but which is of such nature that it cannot be disbelieved,hits the structure, which is then forced to undergo a complete reorgan-ization.

Thus, information is fragmented and transitory, whereas knowledge isstructured, coherent and of enduring significance; furthermore, informationis acquired by being told, whereas knowledge can be acquired by thinking.Any kind of experience—accidental impression, observation and even ‘inner’experience not induced by stimuli received from the environment—mayinitiate cognitive processes leading to changes in a person’s knowledge. Thusnew knowledge can be acquired without new information being received.

2.2. An Interactive Model of Representation of Knowledge andInformation

The above arguments 10 underline the need to come up with a distinctionbetween knowledge and information that is not restricted to a simple stockor flux distinction, and also to come up with a framework that explicitly

introduces some cognitive mechanisms of individuals. This position leads us toan epistemic approach close to constructivism. From the previous perspective,this can be done in three steps:

1. The first step is to abandon the pure linear process of the formation of

FIGURE 1. The linear process of formation of knowledge.

10 ‘To sum up, information in the sense of telling and being told is always different from knowledge inthe sense of knowing: the former is a process, the second a state. Information in the sense of that which isbeing told may be the same as knowledge in the sense of that which is known, but need not be the same.That even in everyday parlance people sense a difference can be seen from the fact that in railroads stations,airports, department stores and large public buildings we expect to find a booth or a counter market“Information” but never one marked “Knowledge”. Similarly in our modern economy, we find many firmsselling information services, not knowledge services. [On this very topic, it seems that what was true whenMachlup wrote it some 20 years ago is true no longer, when considering the development of knowledge-intensive services.] On the other hand, we would frown on education programs that fill the student’s headwith a load of information: we want them to disseminate knowledge of enduring value and to develop ataste or a thirst for more knowledge, not just information.’ (Machlup, 1983)


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knowledge. Knowledge not only results from a one-way cumulative pro-cess (from information to knowledge), but requires continuous feedbackloops between the different main components involved (data, knowledge,wisdom). Each component interacts with the others, and in particular can‘inform’ the others (cf. Figure 2. ‘Inform’ here means that one componentof the system provides to another a specific meaning and volume of information (a quantum of novelty, in quantitative but also qualitativeterms). This vision, in line with Boulding’s point of view, ‘disconnects’ thedirect and exclusive relationship— stock/flux—between knowledge andinformation.

2. The second step is to introduce explicitly some cognitive features of theindividual (that is to abandon the rationalistic hypothesis of the separationbetween the knower and the known). Consequently, the different com-ponents of the process of formation of knowledge must be reconsidered:

‘Data’ can be distinguished in terms of ‘stimulus’ in the case of anemission of data from nature, and ‘message’ in the case of an emissionof data from a human emitter. The main difference between these twokinds of ‘data’ is the following: ‘Nature does not speak’, which meansthat the stimuli are not being organized a priori but will be interpretedand categorized ex post by the cognitive agent. On the contrary, messagesare organized a priori by a cognitive building such as language, categor-ization or classification, even if they also need a further interpretation bythe cognitive agent.

• The second component is constituted by the block ‘knowledge andrepresentations’ that results from a specific structuring of data andmessages that depends on the ‘vision of the world’ of the cognitive entity.The need here to distinguish knowledge and representations comes

FIGURE 2. The interactive system of formation of knowledge and the different processes atstake.


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from the need to distinguish short-term and long-term memory. If bothrepresentation and knowledge result from cognitive structurings bythe agent, representation is contextual and temporary, and has to

do with the mental attitudes in a given context such as ‘how to listento this talk, how to solve this problem, etc.’, which supposes a short-term building, while knowledge corresponds to a more long-term‘sedimentation’.

• The third component, the ‘vision of the world’ of the cognitive entity,corresponds to its wisdom that includes its beliefs, judgements andvalues. These are meta-categories which determine the nature of therules and the direction of the learning processes to be followed by theagent. 11

The relationship between the different components of the system alsohighlights the different processes at stake in the dynamics of the system:classification/categorization, interpretation, application of rules and heur-istics, learning processes, etc. One of the most fertile avenues of researchfor social sciences has been the recognition of the role played by cognitivemechanisms (Ancori, 1992)—memory, pattern recognition, perception,communicative skills—that are instrumental in the interaction betweenexperience and practice on the one side and beliefs and judgements on theother. In this perspective, the definition of the economic agents includes theircognitive abilities and the split between the actor and the processes in whichhe is engaged disappears.

3. The third step is that when explicitly introducing another agent, one can

pinpoint the specific needs for interaction and communication betweentwo agents in the formation, circulation and exchange of knowledge.In this framework (Figure 3 below) some specific issues arise such asthe need for building common languages, common classification andcategorization of messages, and for sharing and building some commonknowledge and some collective learning processes. These characteristicswill be essential when examining the process of codification of know-ledge, and will be analysed in more depth below.

11 In the rationalistic vision individual beliefs are given (Walliser, 1998) and remain unchained throughthe process of quest for the truth. Agents have no cognitive features, because there is no room in thisapproach for any learning process internal to the agent that would shape progressively its set of beliefsfrom the experience gained in the search for knowledge: introducing a process of revision of the beliefsimplies a constructivist vision of information, which is in contradiction with the optimizing methodologyof the Game Theory (Ancori, 1998).


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3. Knowledge as a StructureWhat comes out of the previous section is that (i) knowledge is closelydependent on the cognitive abilities of the actors who hold it and (ii) know-ledge cannot be considered separately from the communication processesthrough which it is exchanged. A third proposal can be added, and this sectionwill be devoted to explaining it: knowledge demands knowledge in order tobe acquired and exchanged. This leads us to understanding knowledge as astructure, which can be broken up into complementary layers. 12 A basicstimulus (‘I feel heat on my skin’) will only be valuable if it goes along withthe knowledge of how to use it (‘I will put on some light clothes’), how toexchange it (‘I can tell to others that the sun is shining’) and how to manageit (‘I should suggest to my friends that we should go to the beach before itbecomes too crowded’). The example is simplistic, but is sufficient to raisethe questions we want to focus on: how is knowledge stored and how doesit trigger actions, what part of knowledge has to be codified, and wherewill knowledge be diffused? To provide some answers, we propose to consider

FIGURE 3. Interaction between agents in the formation of knowledge.

12 At this point, in line what was expressed by Machlup, Saviotti (1998) summarized some of the mainfeatures of knowledge: ‘Knowledge establishes generalizations and correlations between variables.Knowledge is therefore a correlational structure. The extent to such correlation is not infinite. Each pieceof knowledge (e.g. a theory) establishes correlations over some variables and over particular ranges of theirvalues. As a consequence, knowledge has a local character . . . The degree of such local character can bemeasured by the span of a given piece of knowledge, that is, by the number of variables and by theamplitude of the range over which correlation is provided. General theories will have a greater span thana very specific piece of applied knowledge . . . Particular pieces of information can be understood only inthe context of a given type of knowledge. New knowledge, for example relative to radical innovation,creates new information. However, this information can only be understood and used by those who possessthe new knowledge. In other words, knowledge has also a retrieval/interpretative function. In summary,knowledge is a correlational and a retrieval/interpretative structure, and it has a local character’.


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knowledge as a structure comprised of four different layers, ranked in order of increasing complexity:

1. The first layer is ‘crude knowledge’. We have discussed in the previoussection the concept of data. Our main point was to substitute to thisconcept the two notions of stimuli (emitted by nature) and messages(emitted by a human being). As soon as they are perceived by an agent,both constitute the first layer of the structure of her/his knowledge wecall ‘crude knowledge’—i.e. information as an event without meaning.More exactly: information before the building of a meaning by thereceiver, as seen by Shannon and Weaver (1949). This layer of knowledgegathers together elements such as plain facts, messages and intuitions(which are kinds of ‘reflexive’ messages). At this elementary step we con-sider these elements as autonomous pieces of knowledge. The point is notto see if they have been, or how they will be, processed, interpreted orattached to a specific context: ‘I see a ray of sunshine’, ‘my boss told meI’m fired’, ‘the economics of knowledge is a promising research field’ areexamples of elements of crude knowledge. If we think of the learning of a foreign language, the emphasis is put on ‘grasping the word’ before‘getting the meaning’. This is obviously a rather artificial perspective, butuseful to underline a first issue: when considering crude knowledge, whatmatters is the volume of knowledge to be perceived compared with the(scarce) cognitive resources of the agents. For instance, the learningprocesses in collecting crude knowledge elements will be different if theyare highly codified or if their sources are localized in time and/or spacebecause of organizational boundaries or rules.

2. The second layer of the structure of knowledge is the knowledge of

how to use (crude) knowledge. We want to stress two aspects: (i) how anew piece of stimulus/message is integrated with the previous stockof accumulated knowledge and (ii) how action and decision making arerelated to crude knowledge.

Once a stimulus or a message has been perceived, the agent has to resolvethe equivocability of this new piece of knowledge. This is done by a backwardprocess through which the new knowledge is confronted and articulated withprevious experiences.13 Weick (1979) distinguishes three processes: the enact-ment process, in which the knower ‘constructs, rearranges, singles out and

13 We refer to Weick’s representation (1979) of the organizational sense-making process, although acognitivist would certainly disagree completely. But for economic purposes it seems also to be applicableto individuals.


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demolishes many objective features of his/her surroundings’; the selectionprocess, which leads to identifying, rightly or wrongly, the set of causalrelations; and finally the process of retention, which is the memorization of

the successful sense-making.The processes described above lead to a peculiar form of ‘historical’ know-

ledge, ‘stored usually as a map of relationships between events and actions,that can be retrieved and superimposed on subsequent activities’ (Choo,1996). To this extent, action is triggered by the occurrence of a message ora stimulus. But the link can be more or less loose. In some cases, the per-ceived stimulus automatically releases a well-defined action, as in the caseof Pavlovian reflexes. It is the case when previous learning processes have

produced routines; and the more the routines are achieved and adapted, theless understanding is required to justify the undertaken action. 14 Conversely,in some situations, the crude knowledge has first to be articulated withprevious accumulated knowledge which must be retrieved and eventuallyreorganized. Then, if the consequences are not clearly identified, action willbe undertaken step by step, through trial-and-error processes, in order tocollect more knowledge (‘crude knowledge’) about its reliability.

To summarize, the second layer of knowledge sustains the retrieval property

of knowledge, shapes the knowledge by creating a meaning and stimulatesthe production of knowledge of the first layer. The main point here is thefollowing: the appropriation of crude knowledge—i.e. its integration in one’scognitive context—is not the result of a transmission, but rather the result of a re-engineering process. For example, when the receiver knowing ‘blue’ and‘green’ receives the message ‘red’, the result in his/her cognitive context isnot to replace ‘blue’, ‘green’ by ‘blue’, ‘green’, ‘red’, but to replace ‘blue’,‘green’, ‘blue and green’ by ‘blue’, ‘green’, ‘red’, ‘blue and green’, ‘blue and

red’, ‘green and red’, and ‘blue and green and red’. In other words, cognitionfollows combinatory rules, not additive rules, as seen by Bateson (1972).

3. The third layer is related to the exchanges and interactions an agenthas to conduct in terms of knowledge. This category mainly coverscodes, languages and models, which are basically tools used to exchangeknowledge. Thus, knowing how to transmit knowledge implies obviouslythe mastery of codes and/or languages. But it also includes knowledge

about the modes of conversion of knowledge that are the ways throughwhich individual knowledge becomes collective (and reciprocally), tacitknowledge becomes explicit (and reciprocally), two pieces of knowledge

14 March and Simon (1993) defined the concept of performance programs, in which a predefined actionprogram allows the reduction of the requirement for cognitive resources.


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merge, one piece of knowledge splits into two, etc. Thus the individualand collective levels are not independent of each other, but interact witheach other iteratively and continuously. The knowledge about how to

use knowledge clearly activates different types of conversion processes.However, we intend to make a distinction (Steinmueller, 1999) betweenon the one hand the process of extension, that is, the process of using therepresentation and the reproduction process in order to extend know-ledge, and on the other hand the process of representation (the process of creating the codes) and the process of reproduction, that enables thecommunication and the establishment of shared meaning for faithfulduplication. There is an implicit strategic dimension in the second situ-

ation insofar as the adopted codes and modes of conversion should takeinto account the abilities of the receiver. And in this respect, codes, andespecially languages, are not neutral means to transmit knowledge. Theyinclude intrinsically a representation of the world and mobilize differentamounts of cognitive resources, both for the emitter and for the receiver.Furthermore, the strategic dimension also includes the question of theincentives to reveal or to keep secret the code used to process knowledge.

4. The fourth and last layer of knowledge is the knowledge about how

to manage knowledge. This category corresponds to higher cognitivefunctions, which shape the three previously described categories. 15 Themanagement of knowledge supposes the ability to modify even drasticallythe context of production and exchange of knowledge. It thus encom-passes knowledge about when, where and how to ‘find’ relevant crudeknowledge. We mean here knowledge about the localization of know-ledge as well as knowledge about the incentive mechanisms which willbring another agent to deliver messages about what he knows. It includes

also knowledge related to the enactment, the selection and the retentionmodes mentioned in the second layer. Are those processes efficient,should they be improved (and how), are they too costly, etc.? Knowledgeis also needed for the management of communication. The choice of theconversion modes or of the used codes will be according to the use of thetransmitted knowledge the other agents could make. The same typeof choice can insure a relative control on the appropriability of codifiedknowledge. Finally, the management of knowledge also bears on thedegree of interaction between the different subcategories of knowledge.

For illustrative purposes, we can refer to the work of Gibbons et al. (1994).

15 The learning processes at stake come close to the Bateson (1972) third type of learning or thedeutero-learning characterized by Argyris and Schön (1978).


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They assume that the mode of production of knowledge has recently beendramatically transformed, shifting from mode 1 16 to mode 2. The new modeis characterized by a strong transdisciplinarity. It implies also a diffusion over

a wide range of potential sites of knowledge production and different contextsof application creating some discontinuities in the fields of knowledge. Undersuch assumptions, the knowledge to manage knowledge becomes a crucialand strategic resource, able to create decisive advantages in favour of itsholder(s). It can be described by referring to topological representation of knowledge. A given piece of knowledge has a ‘width’, which expresses itsdegree of generality. This degree of generality corresponds roughly to thenumber of actual users of this piece of knowledge (those who have the codes

and language to use it). A given piece of knowledge has also a ‘depth’ whichcorresponds roughly to its degree of complexity. When referring to the degreeof complexity here we mean that there are some pieces of knowledge that, inorder to be manipulated, require large amounts of memory and tacit know-ledge deeply rooted in the practices of the agents concerned. Conducting anorchestra, for instance, certainly requires more ‘depth’ than ‘fixing a nail’. Thedegree of tacit knowledge that needs to be accumulated and then retrieved tobe able to achieve the former activity compared with the latter expresses thisdepth of knowledge. The management of knowledge can thus be seen as theability to adjust the width and the depth of knowledge.

We have thus tried to tackle knowledge as a structure, composed of four interwoven layers. One aim was to avoid associating strictly one typeof knowledge (a product of knowledge) with one knowledge-based activity.Instead, we propose to assess the differences between activities by looking atthe features of the layers we have defined. For instance, the oppositionbetween scientific knowledge and technological knowledge would be moreprecisely addressed using common criteria: what are the sources of knowledgein each case? Is knowledge extracted from human capital or is it collected inthe environment? Is the use of knowledge submitted to strict rules? Is thereroom for ambiguity and superstitious learning? What is the degree of controlexerted on the mechanisms of diffusion of knowledge? This representationshould be helpful in pushing further the analysis of the learning processes.Processes of different nature can be associated with each layer, and the inter-actions between the learning processes are dependent on how the layers areinterrelated. The decomposition of the structure of knowledge should alsoprovide new elements in the understanding of its codification process. For

16 ‘The complex of ideas, methods, values and norms that has grown up to control the diffusion of theNewtonian model of science to more and more fields of enquiry and ensure its compliance with what isconsidered sound scientific practice’ (Gibbon et al., 1994, p. 166).


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instance, the codification of how to use knowledge is different from the codi-fication of how to transmit knowledge. The objectives and the impacts of thecodification are not the same, since the incentives and the strategic behaviours

of the agents differ.However, two central issues still have to be addressed here. The first is that

of the relationship between the tacit dimension and the degree of codificationof knowledge. The second is the collective or individual status of knowledge.These two points were implicitly present all along in the previous considera-tions. We will see that the tacit dimension of knowledge (inherently relatedto the issue of the degree of codification of knowledge) and the collectivestatus of knowledge are crucial features going through all the layers we have

been considering, and they have a strong impact on the understanding of thestructure of knowledge.

4. The Tacit DimensionThe distinction between explicit and tacit knowledge, which was introduced

by Polanyi (1962),17

has a fundamental importance in economic terms.The role of observable knowledge in human activities relies on a significantamount of knowledge which remains hidden. This occult part of the icebergstill has a strong impact insofar as it is mobilized to produce, to use and toexchange knowledge. As this simple statement is increasingly recognized,the concept of tacit knowledge has been used in economic literature to dressall those pieces of knowledge which are not expressed and/or not expressibleand/or not transmittable. As underlined by Cowan et al. (1999), tacitness has

thus become both a portmanteau and a buzzword. We aim here to clarify theconcept somewhat: using our representation of the structure of knowledge,we distinguish two aspects of tacit knowledge, impacting different degrees onthe economic activities.

• First, tacit knowledge can point out specific knowledge, held and shapedby individuals.

• Secondly, tacit knowledge also corresponds to knowledge which is not

17 As mentioned by Spender (1996), ‘while this reflects James’s distinction between knowledge aboutand knowledge of acquaintance, Polyani adds important nuances. Explicit knowledge is like knowledgeabout in its abstractness, while tacit knowledge is associated with experience. But Polyani’s notion of thetacit is richer than mere knowledge of acquaintance, because it brings in a post-Freudian psychologicaldimension, reaching beyond conscious knowledge into the sub and pre-conscious modes of knowing. Hisintent was to criticize the positive norm of doing good science, that one should interact only the explicitlyrationalist and empiricist traditions by formulating logical hypotheses and doing repeatable tests’.


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mobilized (at least consciously) when conducting some activities in agiven context.

Polanyi argued that scientific creativity needs a deep immersion into thephenomena to be explained, for that alone gives rise to intuitions on how tobegin the interaction. As he wrote: ‘I have tried to demonstrate that intoevery act of knowing there enters a tacit and passionate contribution of theperson knowing what is being known, and that this coefficient is no mereimperfection, but a necessary component of all knowledge’. There is thus anindispensable component of all knowledge that has to be taken into accountwhen discussing its formation. For Polanyi, science is a process of explicating

the tacit intuitive understanding that was driven by the subconscious learningof the focused scientist. According to him, the origin of all knowledge residesthus in individual intuition. Without being so categorical, we want to insiston the strong specific dimension of crude knowledge, which depends on theindividual’s perceptive abilities. Thus tacit knowledge in our first categoryexpresses the diversity of the knowledge held by different agents. In otherwords, even if they are faced with the same signal or message, agents willconstitute differentiated stocks of crude knowledge, which can be consideredas tacit knowledge. In this perspective, the concept refers to the fact that whatan agent knows is ignored by all the others.

This approach toward tacit knowledge can obviously be extended to oursecond category, in which knowledge is involved in the sense-making process.More precisely, it seems that, according to Nonaka (1994), one can distin-guish between two main elements, one cognitive, the other technical. Thecognitive elements centre on what Johnson-Laird (1983) called ‘mentalmodels’ in which human beings form working models of the world by creatingand manipulating analogies in their minds. These working models includeschemata, paradigms and viewpoints that provide perspectives or representa-tions which help individuals to perceive and define their world. By contrast,the technical elements of tacit knowledge refer to concrete know-howand rules of action/decision that apply to specific contexts. Once again, weinsist here upon the personal quality of tacit knowledge—without taking intoaccount whether the knowledge is common or shared, transmittable or not.

But there is a second way to understand tacit knowledge by looking athow cognitive resources are used. To specify this inherent relationshipbetween tacit and explicit knowledge, we refer to Polanyi’s classical exampleof craftsmanship: as mentioned by Tell (1997), in order for us to operate withexplicit knowledge in our language, we consider signs, words, grammar,formula, etc., as tools in our argument. Therefore we need knowledge in using


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these tools, the same way the carpenter needs knowledge in using thehammer. When using a hammer to drive a nail, the carpenter attends to bothnail and hammer, but in a different way : ‘I have a subsidiary awareness of the

feeling in the palm of my hand which is merged into my focal awareness of mydriving in the nail’ (Polanyi, 1962). This process, in which we are able to relyon what we are only subsidiarily aware of, is the tacit dimension of knowing.

Tacit knowing is like letting something become a tool for our usage andallow it to become an extension of us. This allowance is what Polanyi calls‘tacit assent’. The tacit assent is purely a-critical, as opposed perhaps toarticulated assent, since it means that the knowing subject surrenders towhat she or he is subsidiarly aware of. Letting something become subsidiaryto one’s awareness involves what Polanyi calls indwelling. (Tell, 1997)

This means that the particulars of knowledge as described here are un-specifiable in explicit knowledge. When attending to what is articulated, wecannot at the same time focus on the process that makes us articulate what weknow.

As in the previous case, tacit knowledge remains hidden. But the differencehere is the degree of intentionality in the use of knowledge. 18 What mattersis not the (natural) specificity of the individual cognitive abilities (which arelargely out of the control of the knower) but much more the way in whicha piece of knowledge interacts with other pieces of knowledge. As Polanyi(1962) emphasized:

the particulars of a skill appear to be unspecifiable, but this time not in thesense of our being ignorant of them. For in this case we can ascertain thedetails of our performance as well, and its unspecifiability consists in thefact that the performance is paralysed if we focus on these details.

Using our own analytical frame, we would say that an agent renders a piece of knowledge tacit because he has the knowledge of how to manage knowledge.As a consequence, tacit and explicit knowledge at a given moment in time aretwo complementary forms of knowledge, but through time their combinationand composition can vary depending on the context and on the degree of attention of the knower who determines which zones of knowledge belong toher/his focal awareness and which zones belong to the subsidiary awareness.

18 The degree of intentionality of the use of knowledge draws back to the concepts of competence andskill. It is even noticeable in the quotation of Polyani we are referring to. Although the question is of primary importance, we do not have enough room here to work it out properly.


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For economists, the distinction between tacit and explicit knowledge has astrong potential operational value: basically, explicit knowledge refers toknowledge that is transmittable in formal, systematic language, while tacit

knowledge has a personal quality which makes it hard to formalize andcommunicate. In our view, this distinction is not sufficient. By entering intomore details on what tacit knowledge is, we should be able to amplify itsfruitfulness. Three analytical challenges can be identified:

1. We have seen that crude knowledge and knowledge about how to useknowledge is highly specific—i.e. those categories incorporate a largeamount of tacit knowledge. On that point, what matters is the degree of diversity generated by tacit knowledge. If knowledge is sufficientlydifferentiated among agents, it raises interactions and triggers mech-anisms for the creation of knowledge. A good illustration is providedby the design constraints of research structures. It is admitted thatin order to be productive, a laboratory has to attain a critical mass of researcher: the justification is to multiply the ways problems are perceivedand tackled. In other words, the organization exploits several stocks of tacit knowledge. Nevertheless the headstone is not the transmission of tacit knowledge (and by implication its formalization) but its coordina-tion: researchers do not mainly need to exchange their own routines andperception abilities, but they must devote them to a common objective.The point we want to make through that example is that in certainsituations the ‘constraint’ of tacit knowledge can be solved by co-ordination mechanisms, rather than by a codification process.

2. A second way to approach tacit knowledge has to do with pure com-munication. Some situations are characterized by a lack of adapted codesor communication media. Knowledge remains tacit because the emitterand/or the receiver have no knowledge about how to exchange know-ledge. This is often the case for industrial know-how in production, whichcannot be capitalized because it cannot be expressed in words by theholders of the knowledge. It thus raises the question of the creation andthe diffusion of codes, languages and models: what is the cost of thecodification process, to which extent can this process be controlled, whatare the conditions of access to the code, how can it be stored? Similarly,the question of the excess of codification emerges. Codes, languages andmodels, even if they are tools to communicate, strongly influence theindividual potentiality of knowledge creation. It follows that if the codifi-cation does not leave enough room for ambiguity and interpretation, itcreates inertia in the production of knowledge.


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3. But knowledge can also remain tacit even if the codes to communicate itexist. If a piece of knowledge is part of a complex structure, it remainssticky (von Hippel, 1993). This is the case, for instance, if we look at

the knowledge held by an expert. Potentially, part of his/her knowledgecan be formalized and transmitted, but in practice it is almost impossible.The appropriate explanation is that knowledge about how to manageknowledge remains tacit. Like the carpenter of Polanyi, the expert knowsthrough long practice which knowledge has to be mobilized and whichknowledge has to be left in the background in order to act or to learnproperly. The difference with the previous situation is that under certainconditions (common history, shared experiences, social or organizational

frame), such a form of tacit knowledge can be communicated and sharedamong the members of a community; and its possession determines theinsiders and the outsiders of the community. In other words, what mattersin this case is the history of the construction of the tacit knowledge.Managing tacit knowledge implies the modification of the time dimen-sion (by intensifying the interactions for instance) more than the trans-formation of the knowledge itself.

We have underlined the relative dimension of tacit knowledge. What is tacitfor an individual (or a community) can be perfectly explicit for some otheractors. In the same way, what is tacit at instant t can be rendered explicit atinstant t + 1. But there is also a relative dimension in the way to deal withtacit knowledge. It is not solely a matter of communication. Depending onthe type of knowledge which is tacit, it is managed and valorized throughcoordination mechanisms, codification processes or a ‘historical socialization’of knowledge.

In accordance with our categorization, we have focused on tacit knowledgebecause it appears at every level of the structure of knowledge. But anothertransverse dimension is still missing: the picture would not be completewithout a specific investigation of the distinction between individual andcollective knowledge.

5. The Collective Nature of KnowledgeWe have emphasized in the previous section the nature of tacit knowledge,suggesting that every agent creates its own virtual reality. Indeed, eachobserver will understand differently a price signal, a natural phenomenon,a scientific result. The same ‘objective’ information can lead to severalinterpretations. In this perspective, we assume that the evolution of the


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knowledge structure held by an agent is dependent on embodied abilities. 19

The cognitive capabilities of the agents (the sense of similarity, the sensitivityto external signals or the imagination) will strongly determine the way in

which knowledge is acquired and accumulated, and further will producedifferent meanings. To this extent, processing knowledge is highly specific andpersonal. The (explicit or implicit) recognition of that matter of fact certainlyexplains why most of the works on the formation of knowledge concentrateon the individual. The rationalistic approach of knowledge is essentially anindividualistic one. The quest for the truth in this perspective is a solitaryadventure. Even Polanyi’s ideas on knowledge are intrinsically related to anindividual.

However, the central role played by individual actors makes the formationand the use of knowledge strongly dependent on the nature of the organ-izational and other collective devices they belong to. As mentioned bySpender (1996), since Simon’s (1957) famous critique of the rational economicman,

there has been wide recognition that the assumption of an atomistic andisolated individual may not serve organizational analysts as well. There aresignificant social, institutional, organizational and economic processeswhich, we now recognize, can only be explained by going beyond suchpresuppositions and cognitive and evolutionary economists are able to workthis ground in good effect.

Two basic reasons can be put forward to justify why individual learningprocesses have to be enclosed within collective processes. The first one isthe localized nature of the personal learning processes (Stiglitz 1987). As the

specialization in the production activities requires an increase of the industrialexchanges, the specificity of the individual knowledge structure compelsinter-personal interactions. If at a given moment in time each individualholds some specific and/or specialized knowledge, there is a need to ‘mobilize’socially all these dispersed elements. This was, for instance, as we have seenin the introduction, the way Hayek conceived the problem of knowledgefor society. Beyond the limitations of Hayek’s vision, 20 he raised an import-ant issue which is the way this ‘networked’ form of knowledge is efficiently

shared and exchanged through interaction between agents. The social19 Nightingale (1998) stresses in peculiar the embodied ability to recognize similarity. This ability is

obviously evolving with learning processes, but part of it is innate, otherwise learning processes wouldnever take place (Pinker, 1994).

20 According to him, the knowledge to deal with is just the existing knowledge: agents are notproducing any new form of knowledge, so the vision is essentially static.


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communication dimension is thus crucial and must be explicitly introducedin the building and use of knowledge. The building of a ‘common knowledge’(Koessler, 1999), the need to set rules and languages to facilitate the collective

formation of knowledge, and the recognition that ‘context’ matters in theprocess of knowledge creation are characteristics that naturally emerge andunderline that knowledge results from a collective construction process (seeFigure 3).

The second reason to consider knowledge as resulting from a social con-struction process is related to one of its peculiar properties. Knowledge is atonce an input and an output of the learning processes. In other words, it isclear that individuals cognize and generate knowledge (once the knowledge

has been produced, the questions of rivalry, exclusion and exchange of the‘output’ are crucial). But it is also clear that the way individuals learn startsfrom, and is shaped by, pieces of knowledge held collectively by thecommunity they belong to. Kuhn’s works on the notion of paradigm areclearly a seminal contribution to this perspective (Callon and Latour, 1991).The Kuhnian paradigm is at once a set of representations of problems andof procedures to solve those problems, and a social group which sticks tothis representation of the world. A similar approach is taken by Wittgenstein(1969), who viewed language as a game of interactions played by multiplepersons following rules. This view is also dominant in the Japanese intellectualtradition about knowledge that has been described by Nonaka and Takeuchi(1995). As underlined by Nightingale (1998), scientists and technologists—and it is certainly also true for every human being—have an understandingabout how the world works, received as part of a learnt tradition that onlyvery slowly divorces itself from the wider traditional beliefs of society.

Both arguments raise the difficult question of the connection between theindividual and the collective level: how will an individual benefit from (andbe guided by) collective knowledge, and conversely, how will the individualknowledge be extracted and socialized. The former point implies analysis of the relation between individual learning processes and the cognitive facilitiesprovided by the collective structure within which they take place. The latterstresses the incentives schemes and the norms associated with the institutionalsettings on which the socialization of knowledge depends. We do not intendhere to tackle in depth organizational learning or coordination/incentivesmechanisms, but looking to the content of knowledge still leads us to turnthe problem into organizational terms. Gibbons et al. (1994) describe em-bedded knowledge as knowledge which cannot move easily across organ-izational boundaries, its movement being a constraint in a given network orset of social relations. Apart from how knowledge circulates within such an


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organization, the analysis has thus to deal with the problem of theidentification of the organizational frontiers and their degree of ‘tightness’. Inother words, the spread of collective knowledge will size the organization.

Furthermore, depending on the type of socialized knowledge, the organ-ization will be more or less opened to outsiders; as a consequence, theorganization will exchange and produce knowledge mainly on the basisof internal learning processes or will also be able to interact with itsenvironment.

In order to focus on the question of organizations as knowing entities, andas we do for the distinction between tacit and explicit knowledge, the wholestructure we propose in section 3 can be split into collective and individual

knowledge. Let us recall once again that we do not aim here to analyse howindividual knowledge is converted into collective knowledge (and vice versa),but rather want to emphasize the impact of the existence of differentiatedsocial types of knowledge.

Looking to the individual learning processes is useful to justify theemergence of collective knowledge within organizational structures. Learningcan be described as a process built on the interplay of four cognitive pro-cedures (Bureth, 1994): the acquisition of knowledge relies on the detection,

the memorization, the evaluation and the creation of knowledge. In thisperspective, an individual agent will find some meaningful resources at thecollective level, especially in terms of memory and of assessment.

The organization can be the ‘depository’ of collective knowledge 21 abouthow to use knowledge, as, for instance, in the case of behavioural rules. Thesefavor single loop learning and also orient and localize the knowledgeactivities. Seemingly, part of the codes and the languages used to com-municate inside the organization are stocked at the collective level. Those

shared communication tools will homogenize the way individual knowledgeis extracted by providing a basis for collective sense-making. Finally, thesocialization of knowledge about how to manage knowledge is a means toframe coherently the individual procedures of conversion from tacit to explicit(and explicit to tacit) knowledge. Nonaka and Takeuchi (1995) have high-lighted the importance of the modes of conversion of knowledge, describingit as the central phenomenon to explain the formation of knowledge.

The socialization of the different categories of knowledge provides alter-

natively a substitute or a complement to individual knowledge. They facilitate21 This research field has been opened among others by Nelson and Winter (1982) in their evolutionary

theory of the firm. They refer to routines as the organization’s genetic material in which the knowledge of an organization is embedded. The organization provides the context in which the tacit and explicit bodiesof knowledge are both selected by interaction with the external economic reality and then stored intoroutines available in particular to future generations of employees.


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learning processes, insofar as they relieve individual cognitive resources.They can induce automatic retrieval of knowledge and/or pre-determinedbehaviours, provide evaluation criteria, facilitate detection of knowledge

and even enhance the creation of knowledge. But in order to grasp fully theeconomics of knowledge-based activities, the analysis has to pay attention tocollective knowledge in the four categories simultaneously. The importanceof distinguishing different categories of knowledge appears immediately bylooking at the socialization of crude knowledge. Collective crude knowledgewill obviously enhance the rough knowledge base on which an individual canapply his/her cognitive capabilities. But the properties of the collective crudeknowledge (e.g. the degree of non-rivalry or of non-exclusion) are strongly

determined by the extent to which agents share knowledge about how to use,transmit and manage knowledge. For instance, we all ‘know’ that E = mc 2.We are all even able to exchange this piece of knowledge. But only the groupof physicists who share the whole structure of knowledge (how to use andmanage it) are able to exploit and valorize this type of knowledge.

This leads us to an important result related to the distinction betweenindividual and collective knowledge. Looking to how the socialization of thestructure of knowledge will be achieved pinpoints a new elementary unit in

the organizational understanding of knowledge processing. Along that linewe follow those authors working on communities of practices or epistemiccommunities. Every organization is made up of many communities of practice, or groups of people committed to the same practice, in whichlearning is not a matter of conscious design or recognizable rationality andcognitive frames, but a matter of new meanings and emergent structuresarising out of common enterprise, experience and sociability—learning bydoing. 22

The concept of epistemic community relies heavily on the socialization of knowledge, emerging through routines and repeated interactions, rather thanencrypted in rules or in an organizational design. They comprise ‘agents whowork on a mutually recognized subset of knowledge issues, and who at the

22 This, at least, is the definition offered by Wenger (1998) in his book on learning, meaning and identitybased on a detailed longitudinal study of insurance claims processors. Wenger refers to three dimensionsto define the community: the first is mutual engagement among participants, involving doing thingstogether, mutual relationships and community maintenance. The second is joint enterprise, involving thenegotiation of diversity among members, the formation of a local code of practice and a regime of mutualaccountability. The third dimension is a shared repertoire that draws on stories, artifacts, discourses,concepts and historical events, reflecting a common history but still leaving space for ambiguity and newrepresentations. Thus a community of practice—drawing on the subconscious, interaction, participationand reified knowledge to act, interpret, innovate and communicate—acts as ‘a locally negotiated regimeof competence’ (Wenger, 1998, p. 137), as ‘shared histories of learning’ (p. 86).


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very least accept some commonly understood procedural authority as essentialto the success of their collective building activities’ (cf. Cowan et al., 1999).

Wenger puts forward two important aspects we take over here: first, the

social construction of knowledge not only relies on how existing knowledgeis shared, but includes also the processes through which the knowledge isobtained. Considering knowledge of how to use, exchange and manageknowledge is a way to do it. Secondly, the concept of community enriches theorganizational representation of knowledge-based activities. The epistemiccommunity is more than a coordination device insofar as it incorporateslearning infrastructures. 23 These embedded infrastructures of learning arebuilt into the routines and the daily practices of members, and feature all the

communities of practice that are to be found within and across organizations.Wenger’s example of insurance claim processors should not be taken to meanthat learning of the sort he describes does not apply to top management,strategists and scientists. Indeed, one of the remarkable early insights of applications of actor network theory in the literature on sociology of sciencewas to show that incremental and radical learning in the R&D laboratory isno different from the processes described by Wenger, locked as it is inroutines, conversations, artifacts, things, memory and stories (Latour and

Woolgar, 1979; Latour, 1986). All these authors suggest that the level of small groups (communities) is essential to understand the process of transformation and transmission of knowledge from the individual to theorganization (and reciprocally). This is the level where the modes of conversion of knowledge are activated, where the translation of local codes toorganizational language (and reciprocally) is made, etc. These pioneeringworks recognize that organizations evolve by adapting the bodies of knowledge shared by their members; they recognize that the organization

must develop common rules, common knowledge, collective learning andincentives schemes to cope with the need for circulation and creation of

23 Wenger identifies three infrastructures which potentially have enough novelty, perturbation andemergence in them to sustain both incremental and discontinuous learning, and both proceduraladaptation and goal monitoring. One infrastructure is engagement, composed of mutuality (supported bysuch routines as joint tasks and interactive spaces), competence (supported by training, encouragement of initiative and judgement) and continuity (supported by reified memory locked in data, documents andfiles, as well as participatory memory unlocked by storytelling and intergeneration encounters). Anotheris alignment, composed of convergence (facilitated by common focus, shared values and leadership),coordination (helped by such devices as standards, information transmission, feedback, division of labourand deadlines) and arbitration (facilitated by rules, policies and conflict resolution techniques). The thirdinfrastructure is imagination, composed of orientation (helped by visualization tools, examples,explanations, codes and organizational charts), reflection (supported by retreats, time off, conversationsand pattern analysis) and exploration (facilitated by scenario building, prototypes, play, simulations andexperimentation).


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knowledge; and that in this respect, many of these processes take place at thecollective tacit level.

This new approach of organizations based on knowledge management

appears clearly in the case of the theory of the firm, where the traditionalconceptions of the firm in terms of processor of information—based mainlyon transaction cost theory—is now questioned by a new vision in terms of processor of knowledge, the competence-based approach. The existence of two alternative visions of the firm raises some fundamental questions: doesthe competence approach bring a complementary or a competing view whencompared with the traditional theories of the firm, in particular the dominanttransaction-based approach? Which of the two approaches is best fitted to

explain what Casson (1998) considers as the main issues addressed by moderntheories of the firm: (i) the boundary of the firm; (ii) the internal organizationof the firm; (iii) the formation, growth and diversification of the firm; and (iv)the role of the entrepreneur? As Langlois and Foss (1996) pointed out, we areconfronted with the choice between, on the one hand, a traditional contrac-tual approach based on transactions, where ‘firms and other institutionsare alternative bundles of contracts understood as mechanisms for creatingand realigning incentives’, and on the other hand ‘a qualitative coordination,that is helping cooperating parties to align not their incentives but theirknowledge and expectations’.

The concept of community of practice should open some promising avenuesof research and permit reconciliation of these two approaches by assumingthat they are complementary pieces for understanding the functioning of thefirm. Amin and Cohendet (1999) assume that firms manage competenciesand transactions simultaneously. First, they choose the domain of their corecompetencies, the governance of which is specifically devoted to knowledgecoordination. Second, after having chosen the domain and directions alongwhich they want to create resources in the long term, they organize theprocess of current allocation of resources and adaptation to the environment.This assumption clearly signifies that there are two main governancemechanisms to be considered by the firm: the mechanism for governingcompetencies which is defined by the need to coordinate knowledge, andthe mechanism for governing transaction which relies on the need tomanage transactions. In other words, the organization of the firm requires adual structure of governance. In this perspective, the role of the communitiesof practice would be to insure a satisfactory level of coherence of the firm(Brown and Duguid, 1991). This hypothesis shows how the introductionof knowledge can lead to renewed visions of traditional bodies of economictheories, but also clearly compels the need for new economic tools.


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6. ConclusionThe above developments suggest different ways to consider the process of codification of knowledge. The first is to consider the process of codificationwithin the framework of a pure economics of information for which know-ledge does not differ from information. In this perspective economic agents(or organizations) do not possess cognitive mechanisms, they speak the samelanguage and all useful economic knowledge is assimilated to ‘knowledge-reduced-to information’. Only cost considerations prevent residual formsof tacit knowledge to be codified. Each new piece of codified knowledgecontributes to increasing the stock of useful economic knowledge andthe combinatorial complexity of this knowledge stock. In this process of transformation where codified knowledge progressively substitutes tacitknowledge, the focus is on the quality of the ‘telegraphic communication’ thatgoverns the replication of knowledge and the ability to examine and assessdifferent combinations of information.

The second one, the keystone of our reasoning, is that knowledge cannotbe regarded independently from the process through which it is obtained.In this perspective, economics of knowledge differs from economics of information in the sense that knowledge is no longer assimilated to theaccumulation of information in a stockpile. This assumption requiresintegration in the analysis of, on the one hand, the cognitive capabilities of the agents and the organizational context in which they are interacting,and on the other hand, the different types of knowledge that are required inorder to process knowledge. It has led us to suggest splitting up knowledgeinto interwoven layers (crude knowledge, and knowledge about how to use,transmit and manage knowledge). From this model of knowledge formation,we can reinterpret some salient features of the codification process:

1. The combination and the composition of tacit and codified knowledgedepend strongly on the context and degrees of attention of the agent orthe organization that manipulates knowledge. This means in particularthat there are contexts in which agents will be willing to spend more oncodification than other contexts in which they would not be so interestedin bearing the costs of codification. It means also that, provided thatagents master the modes of conversion of knowledge, there are contextsin which they would rather use and rely on their tacit knowledge, andcontexts in which they would prefer to use codified knowledge.

2. In this contextual framework, it is clear that all codified knowledgerequires some tacit knowledge to be useful. If this statement implies theexistence of some minimal degree of complementarity between tacit and


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codified knowledge, it does not automatically lead to an absolutist posi-tion on tacitness. In many contexts, only the tacit knowledge involved inmastering a language is needed in order that codified knowledge can

be reconstituted as operational and generative. These are cases whereagents have just to bear the costs of learning the language to acquire theabsorptive capacities to use the codified knowledge.

3. If in this framework the relation between tacit and codified knowledge isneither just a question of complementarity nor just a question of sub-stitutability, it becomes relevant to look at the ways these two forms of knowledge influence each other. It has been underlined that the existenceof a given tacit form of knowledge, of accumulated learning and habits,

and of norms will shape the ways codified knowledge is produced. Butin turn, the way codified knowledge is produced (the nature of thecodes, the types of categorization, the nature of the physical carriers of knowledge, etc.) will also shape the ways learning processes are directed,focused and assimilated. In that sense one can always say that the produc-tion of codified knowledge would imply the production of new formsof tacit knowledge. An example could be found in many industrieswhere the certification processes at stake affect the modes of learning

between firms, as well as the ways quality controls are conducted, etc. Ata different level, one can observe how the use of some advanced codifiedmanuals for learning a new language can be effective in speeding up the(tacit) learning process by allowing simulations, verification procedures,repetition of sentences, etc.

4. The structure of knowledge in four layers that has been suggested in thispaper also explains some nuances in the relationships between codifiedand tacit knowledge. There are types of codification as well as types

of tacit forms of knowledge. Following Cowan and Foray (1997), onecan distinguish in the codification process the building of models, thebuilding of languages and the building of messages. The first categoryessentially belongs to the management level in the structure of know-ledge we propose, the second to the transmission of knowledge and thethird to the use of knowledge. Each category will affect the tacit formof knowledge differently. When models and languages can be consideredas fixed, the production of codified knowledge can essentially be viewedas a substitute for tacit knowledge. The production of new codifiedknowledge will enhance the efficiency of the combinatorial properties of knowledge as well as the possibility to retrieve knowledge. But even insuch a situation of ‘quasi-economics of information’, the context depend-ence could be such that there could be cases in which agents would prefer


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dealing with tacit knowledge. When models are supposed to be given,the transmission of knowledge is critical, the focus being on the socialcommunication process. The question of creation of new codes and of

their control and access becomes the central point of focus. Again therecould be contexts (the case of experts who disclose as much as possible aknowledge which can be rather easily transmitted) where agents prefer tofocus on tacit knowledge despite the ability to use codified knowledge.When models and languages have to be built, the role of communitiesbecomes essential: they are the places where new models are progressivelytested, validated and compared.

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AppendixAs mentioned in the introduction, different typologies of knowledge havebeen proposed by economists. Most of them refer to the tacit/codified natureof knowledge and on the individual/collective dimension. The pluralisticnature of knowledge leads to numerous definitions that sometimes are incontradiction, sometimes overlap, with risk of confusion. We have tried belowto present a synthesis of the main typologies (Spender, Blacker, and Lundvalland Johnson). Of course, such a synthesis is necessarily too schematic, becauseof the variety of forms of knowledge that are difficult to encapsulate within ageneral typology. We propose to present all the typologies according toSpender’s matrix (1996) (Figure 4), which is built precisely upon thisdistinction tacit/codified versus individual/collective. Spender’s matrix depictsfour types of organizational knowledge (objectified, collective, conscious and


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automatic), with regards to the above mentioned distinction. Parallel to thework done by Spender, Blacker (1995) proposed another typology of knowledge (encoded, embedded, embodied, encultured and embrained)which could also be compared to a large extent with Spender’s. Lundvall and

Johnson’s typology (1994), which is inspired by the pioneering work of Machlup (1983) and which distinguishes the following forms of knowledge—

know-what, know-why, know-how and know-who—can also to some extentbe analysed along the distinction tacit/codified versus individual/collective.Some comments for reading this matrix:

1. North-east quadrant: objectified knowledge (arithmetics, logic, physicslaws, etc.) is explicit, codifiable, transmittable without bias throughlanguage and generic. It is that knowledge that constantly evolvesthrough the pursuit of science, which can be learnt in universities andwhich serves as a platform to investigate new empirical phenomena.Blacker refers to this category of knowledge as ‘encoded’ knowledge. InLundvall and Johnson’s typology, objectified knowledge correspondsessentially to the ‘know-why’ (referring to scientific knowledge of principles and laws of motion in nature, in the human mind and insociety).

2. South-east quadrant: collective knowledge (routines, rules of conduct,etc.) is a collectively and tacitly shared knowledge that guides individualas well as collective action, individual’s representations and communi-cations in the organization. This form of knowledge is created byconvention through the collective use in language and action. Blackerdistinguishes at this level two categories of collective knowledge: ‘em-bedded knowledge’, which resides in systemic routines, and ‘encultured

FIGURE

4. Typologies of knowledge from Spender’s matrix.


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knowledge’, which results from the process of acquiring shared under-standing. There is no clear matching at this level with Lundvall and

Johnson’s typology, since their conception of know-how essentially refers

to individuals (see automatic knowledge); but it is certainly at this levelthat we could incorporate as a subcategory the ‘know-who’ (referring tospecific and selective social relations). In particular, in a collective routineone ‘knows who knows what and can do that’.

3. North-west quadrant: conscious knowledge is constituted of the formalknowledge possessed by individuals. This knowledge is the one heldby professionals (physicians, lawyers, economists, etc.) who know theways to perform and use formal methods and are certified in doing so.

Blacker refers to this type of knowledge as ‘embrained knowledge’, whichis constituted by conceptual skills and cognitive abilities. In Lundvall and

Johnson’s typology, conscious knowledge corresponds to the ‘know-what’(referring to the knowledge ‘about’ facts, and also to the knowledge‘that’).

4. South-west quadrant: automatic knowledge is the personal tacit and not-conscious type of knowledge that allows the individual to understand anddevelop explicit knowledge. This refers to the tacit form of knowledge

developed by Polanyi. This form of knowledge is gained through learning.Blacker refers to this type of knowledge as ‘embodied knowledge’. InLundvall and Johnson’s typology, automatic knowledge corresponds tothe ‘know-how’, or knowledge of acquaintance (referring to skills).

The above matrix indicates ‘ideal-types’, every real firm being a mixture of them. Spender acknowledged that

the weakness of the matrix is that it tells us little about how these varioustypes of knowledge interact and thus little about how the firm becomes acontext especially favourable to the interaction of knowledge creation andknowledge application processes. But the modern trend is away from thetacit and towards the explicit, from the craft to the system.


ancori - 2000 - the economics of knowledge

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