changing patterns of knowledge production and the organizational adaptations inside firms ulrich...

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Changing Patterns of Knowledge Production and the Organizational Adaptations Inside Firms Ulrich Witt Evolutionary Economics Group Max Planck Institute of Economics Jena, Germany

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Changing Patterns of Knowledge Production and theOrganizational Adaptations Inside Firms

Ulrich Witt

Evolutionary Economics GroupMax Planck Institute of Economics Jena, Germany

The problem growth of human knowledge is crucial as an enabling factor for economic growth. The abstract logic well-known from NGT, but...

...task to explain in which way, and under what constraints,new human knowledge is generated and can become an economically valuable resource much more involved.

Huge amount of research on - how innovations are created & implemented systemically (e.g., Dalum, Malerba, McKelvey, e.a.), - what engineers knew and did to achieve this (Metcalfe e.a.) - the role entrepreneurship plays in the commercial application and exploitation of knowledge (e.g., Ioannides).

In a most general sense, this research shows that • growth of knowledge (which enables economic growth) becomes feasible through a co-evolutionary process in knowledge technology and supporting institutions

Suggests attempt to characterize the generic features of the co-evolutionary process

In pursuit of this endeavor we will discuss (i) some principles of human knowledge technology (ii) constraints implied by that technology (iii) organizational adaptations inside firms to changing knowledge technology and their economic rationale (as part of the co-evolving supporting institutions)

(i) Principles of (human) knowledge technologyA trivial hypothesis, though often not accounted for:

The sequence of the two modes is not arbitrary

storing on a carrying medium

(active)

stored(inactive)

expressingstored content

(active)

H.1 Knowledge comes in two modes • an active mode as expression (in an act of processing, use, application) of meaningful information • an inactive mode as meaningful information stored in a proper medium

In historical perspective:• originally, the sequence fully integrated in the human brain

learning → human memory → recall & express knowl. by action

• for most part of history the process centered on the inactive mode of knowledge, i.e. possibilities for its extra-somatic storage → invention of - means for embodying knowledge, e.g. in tools, - ways of encoding knowledge and storing it in encoded form, - systematic, epistemic structuring of knowledge (forming categories, logical connections, taxonomies, causal relationships)

H.2 The evolution of human knowledge technology is basically a process of gradual disintegration of this chain

• to deal with active mode of knowledge human action continued to be indispensible...(the very reason for why the existing human knowledgehas to be acquired anew by each generation)

... until recent invention of first ways of active, extra-somatic knowledge manipulation

• the biggest change of human knowledge technology since the invention of writing some 4000 years ago,→ substantial institutional and organizational adaptation needs (to which we will come back)

• yet, not the only feature of evolution of human knowledge technology that triggers co-evolutionary institutional and organizational adapations• to see this we need to proceed to......

(ii) Constraints implied by knowledge technologyA hypothesis well known from the bounded rationality debate:

H.3 The amount of knowledge a single agent is able to process & express per unit of time is bounded by the limited cognitive capacity of the human brain

• evolution of encoding and extra-somatic storing methods then means that a constraint implied by H.3 is weakened:→ amount of accumulated human knowledge (inactive mode) freed from constraints of individual human memory capacity

Accords with stylized fact of epistemic sciences: (1) of an accelerating growth of human knowledge

(de Solla Price 1963, Birdzell & Rosenberg 1986, Ziman 2000)

• not weakened is the constraint implied by H.3 for the active knowledge mode,

as long as human action needed to process/express knowledge

• with an overall growing storage of human knowledge H.3 therefore implies:→ the agents have to increasingly be selective and specialize in the individual knowledge they acquire, hold, and use

Again this accords with stylized fact of epistemic sciences: (2) of an only partial & increasingly specialized individual knowledge (Pavitt 1998)

This implication creates a new economic problem: that of the allocation of specialized knowledge resources (expertise)

Before we can deal with this problem a further implicationof the changes in knowledge technology needs to be recognized:

• Consider the frequent (minimal) qualitative distinction propositional knowledge

(largely codified, overtly accessible) and procedural knowledge

(know how to do, technicalities, etc)

Another stylized fact of epistemic sciences then is that(3) significant share of state-of-the-art technological knowledge is procedural – which means: can only be acquired in training & on the job in research (Martin & Irvine 1981, Salter & Martin 2001, Zellner 2003)

Crucial implication: if training & research involvement is discontinued, the acquired procedural knowledge sooner or later suffers debasement effect (obsolescence)

imagine the guys in this lab who know how to make gas clouds ultra-cold.(Nobel Prize in Physics 2005,Bose-Einstein condensation ofatoms = technology of the future)how long will they keep up with thefurther development of the technicalities required for handling the newly evolving technologywhen leaving, say, for the R&D department of Siemens tomorrow?

(iii) Organizational adaptations inside firms to the changing knowledge technology Given the principles and evolving constraints of human knowledge technology, how does the institutional side of commercial knowledge utilization co-evolve?

• essential to understand: organizational adaptations - are entrepreneurial actions, - occur in the pursuit and follow the logic of an entrepreneurial business conception (i.e. a conception of what business to do and how)

• any business conception presupposes knowledge & skills on the part of the entrepreneur and/or the employees (e.g. on how to develop, produce, market goods and services)

• hence the core question: how is the knowledge relevant for the pursuit of the business conception provided (allocated)?

• in principle, answer not different from ordinary make-or-buy problem (firm vs. market): to the extent to which human action is needed to process/express knowledge, this action can be provided through hiring skilled labor or contracting respective services.• as always, what alternative is chosen depends on costs, not least transaction costs connceted with the alternatives.

• with regard to transaction costs: - comparative advantage in using new knowledge and/or economies to re-using it (Langlois 1999) favor dis-integration, i.e. provision of relevant knowledge expression via market contracts

- agency problems and contractual hazard in, e.g., specifying R&D services (Williamson 1979)) favor integration, i.e. provision of relevant knowledge expression through hiring labor that has acquired the necessary capabilities

• Only with the rather recent invention of first ways of active, extra-somatic knowledge manipulation through machines embodying knolwedge through pre-programming, yet another option to buy the expression of knowledge:

e.g., buying automatized machine tools;by entire medical diagnostics labs...in general, good deal of labor substitution today= substitution of human knowledge expressionby expression of knowledge embodied incapital goods

• Recent revolution in knowledge technology (offering opportunity to buy non-human knowledge expression) still confined to standardized, repetitive expressions that can be pre-programmed (embodied) in machines

• Where entrepreneurial business conception requires non- standardized, knowledge applications and skills like in R&D, the only alternative still is - “make” knowledge in-house (e.g. in R&D department) or - “buy” the corresponding problem-solving services

• In both cases, relevant knowledge is largely procedural

• due to stylized fact (3), latest procedural knowledge can only be provided by scientist/engineers migrating from research to R&D → how to attract them into commercial firms? (Witt & Zellner 2006)

• from the migranting scientists‘ point of view: a sorting decision

entrepreneur in an ownscience-based start-up

employee in incumbentfirm with R&D departm.

• in either case, potential debasement effect of acquired knowledge stock likely to be anticipated by potential migrants → should it be degrading, how to make a decent living in the commercial sphere?

• debasement effect a problem for the hiring incumbent firm too: → how to ensure a continuing transfer of the latest procedural knowledge without blowing up R&D staff?

science-basedstart-up venture

migrating scientistembodies latest procedural knowledge

t

acquiredknowledgedegrades

large, incumbentfirm organization

can afford to hirelatest proceduralknowledge for R&D?

does firmgrowth suffice?

The case of scientist as entrepreneur:

→ unless firm growth suffices, few organizational adaptationsfeasible to escape from knowledge degradation consequences • attract new migrant by offering partnership

but frequent organizational adaptations in a wider sense: • merger (to reach critical size) or acquisition by larger firm

The case of the large incumbent firm with R&D dept.:

• Problem: in highly innovative industries, constant influx of new migrating scientists needed to access the latest procedural knowledge → what to do with the former cohorts?

• organizational adaptation to this problem: designing & actively supporting in-house career track options from R&D to management

• additional benefit of this adaptation: possibility to screen managerial potential& building up managerial resources base in house

• assigning talented employees to entrepreneurial positions may be necessary to prevent revision of initial sorting decision

T i m e O v e r ! T h a n k s !