Networks of knowledge Pier Paolo Saviotti Eindhoven Centre for - - PowerPoint PPT Presentation

Networks of knowledge

Pier Paolo Saviotti Eindhoven Centre for Innovation Studies (ECIS), School of Innovation Sciences, Eindhoven University of Technology Department of Economics, University of Hohenheim, Germany INRA GAEL, Grenoble, France GREDEG CNRS, Sophia Antipolis, France

A general (not complete) definition

• f knowledge
• Knowledge as
• A correlational structure

– Knowledge establishes correlations, or connexions, between variables

• A retrieval/interpretative structure

– Existing knowledge allows agents to retrieve similar knowledge

Units of knowledge

• Defined at different levels of aggregation
• Variables the lowest, but some more

aggregate units can be used, such as technological classes in patents, classifications

• f scientific publications, themes etc.
• Data used: Patents, publications but any text

can in principle be used

A representation of knowledge

• Based on the previous definition knowledge

can be represented as a network

• Nodes/vertices = units of knowledge

(variables, concepts, themes etc)

• Links/edges = correlations /connections/co-
• ccurrence)

Only some variables are correlated

Knowledge as a network

x1 x2 x3 x4 x5 x6 x7 x8 x10 x11 x12 x13 x14 x15 x16

Knowledge dynamics

• New nodes are created as new observables

are discovered and as new variables to represent them are created.

• Connections/correlations between different

variables are subsequently, and not instantly created.

• The network of knowledge has a variable

number of nodes and of links, generally increasing in the course of time.

The knowledge base of firms and

• rganisations
• Knowledge base = collective ((i) and (ii) )

knowledge that firms can use to achieve their

• bjectives.

– (i) it depends both on the elements of knowledge

• f individual members and on their interactions

– (ii) same individuals in different organisations different outcomes

Rhône Poulenc, Hoechst, Aventis

• Rhône Poulenc and Hoechst were previously

mostly chemical firms, but at different times ( end of the 1980s- mid 1990s) decided to become life science companies.

• This change in strategy involved a change in

their KB

• Aventis was created in 1999 from the merger
• f Rhône Poulenc and Hoechst. Its strategy

quickly became to become a pharmaceutical company.

Example: Rhône-Poulenc 90-92

Biotech subset Chemical subset A61K

Example: Rhône Poulenc 96-98

Biotech Chemical subset A61K

KB Hoechst 90-92

Biotech subset Chemical Subset A61K

KB Hoechst 96-98

A61K Biotech subset Chemical subset

KB Aventis

A61K

Aventis summary

• The two firms before the merger changed

their KBs in the direction indicated by the change in strategy

• In intermediate phases the KB was segmented

with the old part (chemical) very weakly connected to the new part (biological)

• After the merger there was followed an

improvement in the integration of the two components of the KB

Variation of network density

Hoechst Rhône-Poulenc Aventis P2 (1993-1995) P3 (1996-1998) P2 (1993-1995) P3 (1996-1998) 2002 Nodes (N) 33 22 31 32 24 Links (L) 55 36 46 54 73 L/N 1.67 1.64 1.48 1.69 3.04

Monsanto (1)

 From foundation (1901) until end of 1970s

= diversified chemical company (agricultural chemicals, polymers, fibres etc)

 End of 1970s important start of strategic

reorientation away from chemistry

 The search for new fields included plants

genetics, pharmaceuticals, products for electronics, fluid technology etc

 Amongst these possible fields plant genetics

emerged as the dominant one

Monsanto (2)

1980s acquisition of knowledge and competencies in 3rd generation biotechnology by alliances and collaborations, M&A Initially life science company (wide rage of products belonging to different markets by common (transversal) knowledge base, biotechnology Later, abandoned the life science company strategy & focused on agrochemistry

Monsanto, First Period <=1979 Chemistry Agrochemistry USPTO Patents

Organic compounds

• - part of the

class 532- 570 series Plant protecting and regulating compositions Compositions: coating or plastic Liquid purification or separation Synthetic resins or natural rubbers -- part of the class 520 series Fabric (woven, knitted, or nonwoven textile or cloth, etc.)

Monsanto 2nd Period, 1980-1985, Agrochemistry, Plant Biotechnology

Stock material or miscellaneous articles

Polymers, plastics & fibers Organic compounds

Synthetic resins or natural rubbers Plant protecting and regulating compositions Drug, bio-affecting and body treating compositions

Monsanto, 3rd period 1986-1996 Life Sciences, Plant Genetics

Organic compounds Compositions Synthetic resins & related

Drug, bio-affecting and body treating compositions Chemistry: natural resins or derivatives; peptides or proteins; lignins or reaction products thereof Multicellular living organisms and unmodified parts thereof and related processes Chemistry: molecular biology and microbiology Drug, bio- affecting and body treating composition s

Mon

• nsanto

santo 4 4th

th pe

period, riod, af after ter 19 1996 96 See Seeds, ds, ge gene netics, tics, agricultur riculture e

Plant protecting and regulating compositions Drug, bio- affecting and body treating compositions Drug, bio-affecting and body treating compositions Multicellular living

• rganisms and

unmodified parts thereof and related processes Chemistry: molecular biology and microbiolog Synthetic resins or natural rubbers -- part of the class 520 series

Organic compounds

Monsanto summary

 ∆ strategy → ∆ KB (minus classes

corresponding to 'old' products + new technological classes corresponding to pharmaceuticals & agricultural chemistry (life science company)

 Only agrochemicals survive now (Seeds &

complementary herbicides)

 Q: How was knowledge used to create

new products?

 Q: vs competitors?

Applications

• Useful to study:
• Firm strategy
• Firm organization
• Mergers and acquisitions
• Divestitures
• Innovation networks

Network of IPC technological classes, biotechnology, 1981-1985

Network of IPC technological classes, biotechnology, 1986-1990

Network of IPC technological classes, biotechnology, 1991-1995

Network of technology classes for biotechnology, 1996–2000

KB properties

• Coherence
• Variety (Knowledge): related (intra-group) and

unrelated (inter-group)

• Cognitive distance

Variety of the knowledge base of biotechnology

Coherence of the knowledge base of biotechnology

Cognitive distance of the knowledge base of biotechnology

Evolution of biotechnology networks

• f knowledge
• A pronounced structural change occurring

– (i) the emergence of new technological classes linked to biology and partly to physics, – (ii) the disappearance or gradual loss of importance of classes linked to the previous knowledge base, organic chemistry, – (iii) the gradual rise in strength of the links between A61K and the emerging classes and the gradual fall in strength of the links between A61K and the older classes, – (iv) a growth in the number of important nodes and of important links, corresponding to an overall process of diversification of the knowledge networks – (v) the persistence of A61K, showing that the new knowledge is used to attain market objectives similar to the past ones in the pharmaceutical, industry.

Applications

• Test of concepts such as technological paradigms,

trajectories, exploration, exploitation

• Technology life cycles, from random to organized search
• Identify knowledge discontinuities, their evolution and

their impact on firm behaviour and performance

• Compare different firms (firm strategies)
• Compare networks of firms and networks of

technological alliances

References

• Saviotti P. P., Knowledge, complexity and networks, in Antonelli C. (ED) Handbook on the Economic

Complexity of Technological Change, Cheltenham, Edward Elgar (2011)



Saviotti P.P., Catherine D., Innovation networks in biotechnology, in Handbook of Bioentrepreneurship, Holger Patzelt, Thomas Brenner, David B. Audretsch (Eds) Springer (2008)



Saviotti P.P., On The dynamics of generation and utilisation of knowledge: the local character of knowledge, Structural Change and Economic Dynamics Vol 18 (2007) 387-408



Nesta LLJ, Saviotti P.P., Firm knowledge and market value in biotechnology, Industrial and Corporate Change, Vol 15, 625-652 (2006)



Pyka A., Saviotti P., The evolution of R&D networking in the biotech industries, International Journal

• f Entrepreneur and Innovation Management Vol. 5 (2005) 49-68.



Saviotti P.P., de Looze M.A, Maupertuis, M.A., 'Knowledge dynamics and the mergers of firms in the biotechnology based sectors, Economics of Innovation and New Technology, Vol. 14 (2005) 103- 124.



Nesta L.J.J, Saviotti P.P., Coherence of the knowledge base and the firm’s innovative performance: evidence from the US pharmaceutical industry, Journal of Industrial Economics, Vol 53 (2005) 105- 124.



Saviotti P.P.,Considerations about knowledge production and strategies, Journal of Institutional and Theoretical Economics 160 (2004) 100-121.



Saviotti P.P., De Looze M.A, Maupertuis, M.A., Nesta L.. ‘Knowledge dynamics and the mergers of firms in the biotechnology based sectors, International Journal of Biotechnology, VOL. 5 (2003) 371- 401.

IPC Technological classes biotechnology

BIOTECHNOLOGY

A01H new plants or processes for obtaining them; plant reproduction by tissue culture techniques A61K preparations for medical, dental, or toilet purposes C02F treatment of water, waste water, sewage, or sludge C07G compounds of unknown constitution C07K peptides C12M apparatus for enzymology or microbiology C12N micro-organisms or enzymes; compositions thereof C12P fermentation or enzyme-using processes to synthesise a desired chemical compound or composition or to separate optical isomers from a racemic mixture C12Q measuring or testing processes involving enzymes or micro-organisms; compositions or test papers thererof; processes of preparing such compositions; condition-responsive control in microbiological or enzymological processes C12S processes using enzymes or micro-organisms to liberate, separate or purify a pre- existing compound or; processes using enzymes or micro-organisms to treat textiles or to clean solid surfaces of materials G01N investigating or analysing materials by determining their chemical or physical properties

IPC classification

• A Human Necessities
• B Performing Operations; Transporting
• C Chemistry; Metallurgy
• D Textiles; Paper
• E Fixed Constructions
• F Mechanical Engineering; Lighting; Heating;

Weapons; Blasting

• G Physics
• H Electricity

IPC classification (2)

• Site for more detailed IPC classification
• http://www.wipo.int/classifications/ipc/ipc8/?l

ang=en