The Evolution of Biotechnology as a Knowledge Industry: Network Movies and Dynamic Analyses of Emergent Structure Walter W. Powell Douglas R. White Kenneth.

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Presentation transcript:

The Evolution of Biotechnology as a Knowledge Industry: Network Movies and Dynamic Analyses of Emergent Structure Walter W. Powell Douglas R. White Kenneth W. Koput Stanford 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 in relation to both firm-level organizational and financial changes.

Network Movie: 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,

Figure 3: Rapid Phase Transition in Bicomponent Growth

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

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

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

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

Figure 6: Scatterplot of Biotech degree as chosen by other Biotechs (1-Mode) and as chosers of 2-Mode Partners (v2log= v1og; R-Square=0.15)

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

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

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

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.

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

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

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

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