the evolution of biotechnology as a knowledge industry: network movies and dynamic analyses of...

The Evolution of Biotechnology as a Knowledge Industry: Network Movies and Dynamic Analyses of Emergent Structure

• Walter W. Powell Douglas R. White Kenneth W. KoputStanford University UC Irvine University of Arizona

Slides by Douglas R. White

• Biotechnology as a knowledge-based industry involves extensive reliance on organizational learning. This occurs through networks of dense collaborative ties among organizations. We model the emergence of the industry network of contractual collaborations from 1988-99 in relation to both firm-level

organizational and financial changes.

Network Movie: 1988-99• The following twelve slides show the evolution of

collaborative contracts within the biotech industry

• Green ties =Finance

• Red ties =Res&Dev» Grey =Finance

» LiteBlue =Biotech

» Yellow =Pharmaceuticals

» Orange =Res.Labs and Universities

» DarkBrown =Government (e.g., NIH)

» Pink =Miscellaneous

1988: Lots of

Finance,

little R&D

1989: Nucleus of

R&D attracts

more Finance

1990: Massive

investment

in R&D

1991: The phase

transition

is complete

1992: …and then

it stops

1993:

1994:

1995:

1996:

1997:

1998:

1999:

Figure 1: Levels of Network Cohesion: Tricomponents (within dark/red circles) embedded in

Bicomponents (circled in medium/green) within Components (in light/yellow circles)

Figure 2: Slow Transitions to Giant Components,1990-1994

0

200

400

600

800

1000

1200

1400

1600

1800

1983 1985 1987 1989 1991 1993 1995 1997 1999

1-comp

1-mode

482edges

edges

2-mode

3112edges

Figure 3: Rapid Phase Transition in Bicomponent Growth

0

100

200

300

400

500

600

700

1988 1990 1992 1994 1996 1998

R&D

Lic

Finance

Comm

R&D/Lic/Comedge frq

Figure 4: Degree(+1) Distributions for the 1-Mode Data

1

10

100

1000

1 10 100 DBF degree 10 (482 biotech firms)

freq

uenc

y

Figure 5 a: Degree(+1) Distributions for the 2-Mode Data

1

10

100

1000

10000

1 10 100# Links (plus 1)

# O

rga

niz

ati

on

s

482dbf

partners

Figure 5 b : Degree(+1) Distributions for the 2-Mode Data(removing zero frequency counts)

1

10

100

1000

10000

1 10 100# Links (plus 1)

# O

rga

niz

ati

on

s

482dbf

partners

Figure 5 c: Exponential for DBFs' degree choosing partners; power-law for partners degree chosen by DBFs

1

10

100

1000

10000

0 5 10 15 20 25 30 35

482dbf

partners

dbf*.85

part 0̂.9

Figure 6: Scatterplot of Biotech degree as chosen by other Biotechs (1-Mode) and as chosers of 2-Mode Partners

(v2log=.55+0.52v1og; R-Square=0.15)

Degree Correlation for Biotech Firms

1

10

100

1 10 1001-mode

2-m

od

e

Figure 7: The Sexta-component of R&D and Finance Contracts in the Biotech Industry Blue=Biotech, Size of nodes reflects number of finance ties. Brown=government Orange=Research Institutes and Universities Yellow=Pharmaceuticals (f=DBF p=partners)

Figure 7: The Sexta-component of R&D and Finance Contracts in the Biotech Industry Blue=Biotech, Size of nodes reflects number of finance ties. Brown=government Orange=Research Institutes and Universities

Yellow=Pharmaceuticals (f=DBF p=partners)

Figure 8: 1988

Figure 8: 1989

Figure 8: 1990

Figure 8: 1991

1 2 3 4 5 6 7 8 9 10 11-0.1

-0.05

0

0.05

0.1

0.15

0.2

0.25

Figure G1: Time Series of Growth Parameters: Mean Growth by Tie Activity, Separately for Form of Partners.

1 2 3 4 5 6 7 8 9 10 11-0.1

-0.05

0

0.05

0.1

0.15

0.2

0.25

Figure G2: Time Series of Growth Parameters: Mean Growth by Partner Form, Separately for Type of Activity.

1 2 3 4 5 6 7 8 9 10 11-0.1

-0.05

0

0.05

0.1

0.15

0.2

0.25

1 2 3 4 5 6 7 8 9 10 11-0.1

-0.05

0

0.05

0.1

0.15

0.2

0.25

Figure G2: Time Series of Growth Parameters: Mean Growth by Partner Form, Separately for Type of Activity.

1 2 3 4 5 6 7 8 9 10 11-0.1

-0.05

0

0.05

0.1

0.15

0.2

0.25

1 2 3 4 5 6 7 8 9 10 11-0.1

-0.05

0

0.05

0.1

0.15

0.2

0.25

Figure G1: Time Series of Growth Parameters: Mean Growth by Tie Activity, Separately for Form of Partners.

• Left Figure Plots Coefficient of Variation over time for Modal Combinations: Magenta = R&D to Universities and NonProfits, Red = R&D to Government, Green= Finance to Financial, Cyan = Commercial to Biotech, Blue = Commercial to Pharmaceutical and Other For- Profit.

•Right Figure Plots Coefficient of Variation for all remaining combinations with no color legend.

1 2 3 4 5 6 7 8 9 10 11-50

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11-150

-100

-50

0

50

100

Figure 9: Cycles of Learning and Organizational Returns (Powell et al. 1999)

Legend 1. Ovals represent network properties, rectangles are performance and outcome measures, while rounded rectangles can be treated as either firm characteristics or outcomes. 2. Shadowed components carry over from Powell et al. (1996).

Figure 10 a: Finance and R&D networks of 2219 organizations 1988-1991

Figure 10 b: Finance and R&D networks of 2219 organizations 1992-1995

Figure 10 c: Finance and R&D networks of 2219 organizations 1996-1999

Figure 11: Distance from NIH: R&D and Finance