Amphibious Entrepreneurs
and the Emergence of Organizational
Forms*
Walter W. Powell
Kurt Sandholtz
Stanford University
2012
This work appears in two formats, as chapter 13 in The Emergence of
Organizations and Markets, J. Padgett and W. Powell, Princeton University
Press, 2012, and in a different form in Strategic Entrepreneurship Journal,
in press.
Motivating questions:
•
What fosters the emergence of and variety among
organizational forms?
Form: the set of characteristics that identify an organization as both
a unique entity and a member in a group of like entities (Romanelli
1991)
•
In what ways might a pragmatist account of
entrepreneurship challenge and/or complement
prevailing perspectives? Put differently, what arguments
are less heroic and instrumental, more boundedly agentic
and improvisational, and more theoretically compelling? If
we avoid sampling on the dependent variable (looking only
at success stories), can we discern which elements
combine, in novel ways, to produce “fresh action”?
2
Mechanism of novelty #1: Recombination
• Innovation is an interstitial phenomenon
• Tools, concepts, and practices from one domain are
combined with those of a proximal domain
• Reassembly of known elements generates many
technological and organizational innovations
• Ample theoretical and empirical support (Arthur 2009,
Nelson and Winter 1982, Schumpeter 1942)
3
Mechanism of novelty #2: Transposition
• Transposition creates new interstices
• Tools, concepts, and practices from one domain are
introduced into settings where they are foreign
• The assembly of previously unrelated practices can
produce social invention
• Less frequent, and much less likely to be successful
• But even failures at transposition can generate
experiments that have profound tipping effects
6
Amphibious entrepreneurs
• Simultaneously occupy positions of influence in two
distinct domains
• Act as agents of transposition, carrying practices,
assumptions, and decision premises across domains
• As such, often seen as “trespassers” or “rule creators”
(Becker 1963)
• not boundary-spanners doing import/export
• not “strategic actors” engaging in arbitrage
• Play a crucial, albeit unintentional role in the emergence
of novel forms
10
A pragmatist view of entrepreneurship
• When established routines prove lacking, people search
and experiment (Dewey, 1938; Becker, 1986; Stark, 2009)
• People have little choice, however, but to draw on their
stock of existing knowledge to cope with situations without
precedent
• Existing knowledge and routines in new settings offer the
possibility of novel social arrangements
11
Empirical setting: the invention of a new model of
organizing - - the DBF
• The “dedicated biotech firm” (DBF) emerged in the early ‘70s
• Distinct from corporate hierarchies, universities, and government labs,
but with practices transposed from each:
• fundamental scientific research
• horizontal structure of information flow
• project-based organization of work
• porous organizational boundaries
• strong protection of intellectual capital
• unprecedented venture financing (quantity and duration)
12
Fertile ground for studying emergence of
new organizational forms
“It was like maybe a dam waiting to burst or
an egg waiting to hatch, but the fact is, there
were a lot of Nobel Prizes in molecular
biology, but no practical applications.”
-- Ron Cape, Cetus co-founder
13
Political and economic conditions
complemented scientific advances
• Massive political support for university-industry tech
transfer, most notably Bayh-Dole Act passed in 1980
• Diamond v. Chakrabarty (1980) Supreme Court decision
permitted patenting of man-made living organisms
• ERISA and “Prudent Man” rulings permitted pensions
and endowments to be invested in high-risk VC funds
• But poisedness does not imply predictability, nor
dictate potential outcomes
14
No evidence of a biotech blueprint borrowed
from ICT or physical sciences
“We were naïve. I think if we had known everything
about all the potential huge competitors, we might not
have even done it. One of the benefits we had, I
suppose, was some combination of naïveté and ambition
and this desire to do something on our own. I think there
was a feeling of a green field, and that we were the
first…We did not have the business model mapped out,
or the ultimate value proposition, which are all things that
we do today in doing a startup.”
-- Brook Byers, VC & 1st CEO of Hybritech
15
Why we chose to study the first decade
• 1972 provides a natural starting point
• Seminal papers on rDNA presented at conferences
• First bioscience firm founded: Cetus
• By 1981, legal and political foundation was in place
• After 1982, serial entrepreneurs began founding second
biotech ventures (replication of early models)
• Limits of archival record: pioneers attract more attention,
easier to find contemporary accounts of their founding
16
Table 1: DBFs founded in the first 10 years
Company
Cetus
Enzo Biochem
Genentech
Genex
Biogen
Hybritech
Centocor
Molecular Genetics
Seragen
Amgen
Codon
Cytogen
DNAX
Genetic Systems Corp.
Genetics Institute
Chiron
Genzyme
Immunex
ImmunoGen
Integrated Genetics
Repligen
California Biotechnology
SIBIA
Synergen
Xoma
ZymoGenetics
Founding
Year
1972
1976
1976
1977
1978
1978
1979
1979
1979
1980
1980
1980
1980
1980
1980
1981
1981
1981
1981
1981
1981
1981
1981
1981
1981
1981
Location
Berkeley, CA
New York City, NY
South San Francisco, CA
Rockville, MD
Zurich, and Cambridge, MA
San Diego, CA
Philadelphia, PA
Minneapolis, MN
Hopkinton, MA
Thousand Oaks, CA
South San Francisco, CA
Princeton, NJ
Palo Alto, CA
Seattle. WA
Boston, MA
Emeryville, CA
Boston, MA
Seattle, WA
Cambridge, MA
Framingham, MA
Cambridge, MA
Mountain View, CA
San Diego, CA
Boulder, CO
Berkeley, CA
Seattle, WA
Currently
Acquired by Chiron (1991)
Independent
Subsidiary of Roche (2010)
Acquired by Enzon (1991)
Merged with Idec to form Biogen Idec (2003)
Acquired by Eli Lilly (1986) then Beckman Coulter (1995)
Subsidiary of Johnson & Johnson (1999)
Acquired by Eisai (2008)
Acquired by Ligand (1998)
Independent
Acquired by Berlex (U.S. arm of Schering AG) (1990)
Acquired by EUSA (2008)
Acquired by Schering-Plough (1982)
Acquired by Bristol-Meyers (1987)
Acquired by Wyeth (1996), which Pfizer acquired (2009)
Acquired by Novartis (2006)
Subsidiary of Sanofi-Aventis (2011)
Acquired by Amgen (2002)
Independent
Acquired by Genzyme (1989)
Independent
Subsidiary of Johnson & Johnson (2003)
Acquired by Merck (1999)
Acquired by Amgen (1994)
Independent
Subsidiary of Bristol-Meyers Squibb (2010)
17
Method: Multi-case comparison
• Reliance on accounts made in the 1970s and ‘80s by
the founders (in newspapers, magazines, TV
interviews, annual reports, IPO prospectuses, etc.)
• 2,000 plus pages of oral histories in UC Berkeley
Bancroft Library collection
• Excellent science journalism and scholarship
chronicling the era (Kenney 1986; Hall 1987;
Teitelman 1989; Wright 1994; Robbins-Roth 2000;
Vettel 2006)
• Supplemented by our own interviews with founders,
board members, and VCs
18
Table 2: Summary of data sources
Data Source
Data Type
Companies included
Regional Oral History Office,
UC-Berkeley
Bancroft Library
# of pages
analyzed
First-person accounts of scientists, venture capitalists, 2,000+
executives, and employees of the earliest biotech
firms
Lexis/Nexis U.S. newspaper
database, ABI Inform
Journalist accounts of the companies and their
founders
950+
All
American Men and Women of
Science
Mergent Business Profiles
(formerly Moody’s)
Brief biographies of notable scientists
18
N/A
Annual summaries of corporate information, including
characterization of business focus and major
agreements with research or commercialization
partners
100+
All except Codon, DNAX
and Zymogenetics (which
were not publicly traded)
edgar.gov, Lexis/Nexis SEC
database
S-1 (IPO prospectus), 10K (financial results), Annual
Reports
300+
All except Codon, DNAX
and Zymogenetics
ISI Web of Science
Publication counts and citation analysis
N/A
All
Books (industry analyses,
founder biographies, etc.)
First- and third-person versions of the founding stories 1,500+
of the earliest biotech ventures
All
Primary data
Semi-structured telephone interviews
Codon, Genex, Genzyme,
Immunex, Integrated
Genetics, ZymoGenetics
200+
Amgen, Genentech,
Centocor, Chiron, Cetus,
Hybritech, DNAX
19
Sequence of analysis
1. Developed detailed case histories of each company’s
founding
2. Distilled salient attributes and practices within each
case
3. Cross-case comparison yielded 28 unique DBF
practices; consolidated and winnowed to 13 practices
that were shared by at least five of the firms
4. Coded all companies for the presence/absence (1/0) of
these practices
20
Attributes present in more than half the companies
Attribute
Basis for code = 1
Sources
1. Research contracts Research contracts cited as a critical source of
with large
operating revenue.
corporations
2. Noted scientist(s)
At least one founder listed in American Men &
Women of Science 1
Mergent reports, BioScan
directory, SEC filings,
newspapers, and books
American Men & Women of
Science, 23rd ed. , 2007.
3. “Just-off campus”
location
Original company address located within 10
driving miles of the research institution with which
scientific founder(s) associated.
Google Maps
4. Amphibious
scientist(s)
At least one founder was a company officer and
Oral histories, newspapers,
(a) occupied an academic position simultaneously, books, American Men & Women
or (b) returned to full-time academic research later of Science, and SEC filings.
No. (%) of
firms for
which
code = 1
21
(81%)
19
(73%)
18
(69%)
14
(54%)
21
Attributes present in more than a third of the DBFs
Attribute
Basis for code = 1
Sources
No. (%) of
firms for
which
code = 1
5. Non-therapeutic
focus
Company’s espoused strategy centered on
diagnostics, vaccines, or other non-therapeutic
products.
Mergent reports, SEC filings,
newspapers, oral histories
6. Non-traditional
initial public offering
Firm went public prior to having (a) any products
in its pipeline and/or (b) any patented intellectual
property.
USPTO patent database; SEC
filings, Mergent reports,
newspapers
7. Pharma veteran
hired to run the
company
Within the first five years, company hired an
experienced pharmaceutical company executive
as president or CEO.
Newspapers, oral histories,
books
8. All-Star Scientific
Advisory Board
Firm (a) had a scientific advisory board (SAB)
SEC filings, oral histories,
separate from founders, and (b) this SAB included newspapers, and books.
at least one renowned scientist
9
(35%)
9. Scientist in charge
Academic scientist served as president or CEO at
some point during first three years of company’s
existence.
9
(35%)
SEC filings, Mergent reports,
oral histories, newspapers, and
books
11
(42%)
11
(42%)
10
(38%)
22
Attributes present in five or more of the DBFs
Attribute
Basis for code = 1
Sources
10. Encouraged scientific
publication
Firm’s publication record was above the
ISI Web of Science (accessed
sample median on both quantity and quality electronically, October 2010)
measures.
11. Prior entrepreneurial
experience
At least one founder had been involved in a Oral histories, SEC filings,
prior start-up.
newspapers
12. Growth through
acquisition
Within the five years following its founding,
the firm made at least one acquisition .
Mergent reports, newspapers,
SEC filings
13. Venture capitalist served Venture capitalist (a) occupied executive
Oral histories, newspapers,
in operational role
role, or (b) actively intervened in day-to-day books
operations.
No. (%) of
firms for
which
code = 1
8 (31%)
7
(27%)
6
(26%)
5
(19%)
23
1972
1976
1976
1977
1978
1978
1979
1979
1979
1980
1980
1980
1980
1980
1980
1981
1981
1981
1981
1981
1981
1981
1981
1981
1981
1981
Bay Area (Emeryville)
Bay Area (South SF)
NYC
D.C. (Rockville, MD)
San Diego
Boston
Minneapolis
Boston (Hopkinton)
Philadelphia
Bay Area (Palo Alto)
Boston (Cambridge)
Seattle
Thousand Oaks
NJ (Princeton)
Bay Area (South SF)
Boston (Framingham)
San Diego
Bay Area (Berkeley)
Bay Area (Emeryville)
Seattle
Boston (Cambridge)
Bay Area (Mt. View)
Boulder, CO
Seattle
Boston
Boston (Cambridge)
81
80
80
82
81
82
82
92
82
86
81
83
86
83
96
86
83
83
86
83
86
86
89
1
1
0
1
0
1
1
1
1
1
1
1
0
1
0
1
0
0
1
1
1
1
1
1
0
1
AM
PH
IBI
OU
AL
SF
L -S
OU
TA
ND
RS
PU
ER
AB
BL
ISH
(hAC
ind
AD
ex)
SC
I
E
NT
JU
ST
. IN
OF
CH
FC
AR
R&
AM
GE
DC
PU
ON
SL
OC
TR
AC
AC
AT
TIV
ION
T
S
EV
C
"V
AP
OR
" IP
GR
O
EW
BY
AC
EN
QU
TR
EP
T
RA
SR
CK
.P
RE
HA
CO
RM
RD
NO
AM
NT
N
GR
HE
RA
. FO
CU
S
YE
AR
AC
QU
IRE
D
AM
WS
IPO
YR
.
LO
CA
T IO
N
DE
D
FO
UN
CO.
Cetus
Genentech
Enzo
Genex
Hybritech
Biogen
MGI Pharma
Seragen
Centocor
DNAX
Genetics Institute
Genetic Systems Corp.
Amgen
Cytogen
Codon
Integrated Genetics
SIBIA
Xoma
Chiron
Immunex
Repligen
Scios
Synergen
ZymoGenetics
Genzyme
Immunogen
1
1
0
0
1
1
1
1
0
1
1
0
0
0
0
1
0
0
1
0
1
1
1
1
0
0
1
0
0
1
0
1
0
0
0
1
0
0
1
0
0
1
1
0
0
0
0
0
0
0
1
1
1
1
0
0
0
1
0
0
0
1
1
0
0
0
0
0
0
0
1
1
1
1
1
0
0
0
0
0
1
0
0
1
1
0
0
0
0
1
0
0
0
0
0
0
1
1
1
0
1
1
0
0
1
1
0
0
1
1
0
0
1
1
1
1
0
0
1
0
1
1
1
1
1
0
1
1
1
1
1
1
1
1
1
1
1
0
0
1
1
0
1
1
0
1
1
1
1
1
1
1
1
1
0
1
0
1
0
0
1
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
1
1
1
0
0
0
0
1
0
1
0
0
1
1
1
0
0
1
1
1
0
0
1
1
0
0
0
0
0
0
1
1
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
1
1
0
0
1
0
1
0
0
1
0
0
0
0
1
1
0
0
1
1
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
1
0
0
0
1
0
1
0
1
1
1
1
0
1
0
0
0
0
0
0
1
1
1
0
1
1
1
0
1
0
1
0
0
1
0
0
1
1
0
0
0
0
1
0
1
0
0
0
92
09
91
85
08
98
99
82
97
87
08
90
90
99
06
01
03
94
88
-
24
Hierarchical cluster analysis (HCA)
1. Multivariate technique originally used to create phylogenetic trees
from taxonomic data; subsequent uses range from medical image
analysis to market research
2. Useful for samples where 8 < n < 100 (“tweeners”)
3. Accommodates both a rich reconstruction of each firm’s founding
story and a rigorous cross-case analysis of how practices cohered
4. Why not QCA?
•
Binary coding allows crisp-set analysis; “fuzzy logic” QCA not
necessary
•
QCA most useful for determining multiple pathways to outcomes; our
focus is less on outcomes and more on processes by which practices
were combined
•
Deep knowledge of the cases both precedes and follows HCA in the
sequence of our analysis
25
How we used HCA
1. Input: rectangular matrix of 26 firms x 13 practices
2. Intermediate step: square matrix of mathematical
dissimilarity between each pair of biotech firms
3. Output:
•
“Textual dendrogram” showing how clusters of firms
begin to cohere around common sets of practices
•
Tree diagram graphically depicting the clusters
•
Measures of cluster adequacy to help determine
“where to cut the tree” (i.e., optimal level of
homogeneity within and heterogeneity between
clusters)
26
Textual dendrogram (aka “icicle diagram”)
We selected four clusters as the optimal level of agglomeration
27
Figure 3: Selecting the optimal number of clusters
1.2
Adequcy of Fit
(E-I Ratio)
1
0.8
0.6
“Elbow” suggests optimal number of clusters. At < 4 clusters,
all firms rapidly lump together. Beyond 4 clusters, the degree
of internal dissimilarity decreases much more slowly.
0.4
0.2
0
0
5
10
15
20
25
Number of Clusters
E-I ratio =
(# of attributes shared with firms outside the cluster – # of attributes shared with firms within the cluster)
# total shared attributes
(Krackhardt and Stern, 1988)
Branches of the DBF Tree
2
1
3
4
The Dedicated
Biotech Firm
NO
NO
TA
TA
BLE
BLE
SC
SC
AM
A
MP
IEN
IEN
PH
H
T IF
T IF
IBI
I
BIO
IC
IC
OU
F
F
PR
P
U
O
R
S
S
OM
UN O M
FO
FO
D I
UN
UN
INE
D E P ER NENT
DE
NT
PU
R UB
SC
S
BL
C
L
IEN
IEN
ISH
ISH
CE A
CE
ED
ED
AC
AD CA
A
IN
IN
AD
VIS D E
1 st
1 st
EM
O M
5Y
5Y
IC S
R S JU RY B IC SC
R
JU
C
STST- OA IE
I
E
N
N
OF
OF R D T I
T IS
F-C
F-C
ST
T I R&
R&
AM
AM
I
N
DC
D
C
P
P
H
C
U
U
A O
ON
SL
SL
TR
OC AC R GE NTR
OC
AC
AC
AC
AT TI
TIV
T
T
V
ION E
S
S
EV
VC
C
IPO
IPO
w/
w/
oP
oP
RO
RO
GR
G
R
DU
DU
EW
EW
C
CT
TS
BY
BY
SO
O
A
A
RE
R P RE P
R
CQ
CQ
PE
UIS
UIS
AT EA
AT
E T
ITI
ITI
EN
O N H NTS ENT
ON
HIR
TR
I
R
RE
EP
E
ED
P
D
RE
RE
SR
SR
NE
NE
.P
.
P
U
U
NO
N
H
H
R
O
AR
AR
N-T
N
MA
TH
MA
HE
ER
RA
EX
EX
A
EC
PE
PE
UT
UT
IC
IC
FO
FO
CU
S
N
ATTRIBUTES
---------------------------------------------------------------------------------------------------------------------------------------------------------------------Amphibious-founder firms (Cluster 1) 13 1.00 0.92 0.23 0.54 0.54 0.77 0.92 0.08 0.46 0.15 0.15 0.08 0.31
N
Ex-pharma-led firms (Clusters 2, 3, & 4) 13 0.46 0.15 0.46 0.08 0.15 0.62 0.69 0.31 0.38 0.31 0.38 0.69 0.54
---------------------------------------------------------------------------------------------------------------------------------------------------------------------Total: The Dedicated Biotech Firm (DBF) 26 0.73 0.54 0.35 0.31 0.35 0.69 0.81 0.19 0.42 0.23 0.27 0.38 0.42
---------------------------------------------------------------------------------------------------------------------------------------------------------------------firms (Cluster 1) 13 1.00 0.92 0.23 0.54 0.54 0.77 0.92 0.08 0.46 0.15 0.15 0.08 0.31
“In Amphibious-founder
business to do science”
Table 5b: Aggregate Attribute Profiles for the Three Ex-Pharma-Led Clusters
“In science to do
Ex-pharma-led
firms (Clusters 2, 3, & 4) 13 0.46 0.15 0.46 0.08 0.15 0.62 0.69 0.31 0.38 0.31 0.38 0.69 0.54
business”
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Cluster
6 0.73
0.33 0.54
0.33 0.35
0.67 0.31
0.00 0.35
0.00 0.69
0.83 0.81
0.83 0.19
0.67 0.42
0.50 0.23
0.17 0.27
0.17 0.38
0.83 0.42
0.33
Total: The Dedicated Biotech Firm
(DBF)2 26
Cluster 3
3
0.67 0.00 0.00 0.33 0.33 1.00 0.00 0.00 0.33 0.00 0.33 0.67 1.00
Table 5b: Aggregate Attribute
Profiles for the Three Ex-Pharma-Led Clusters
Cluster 4 4 0.50 0.00 0.50 0.00 0.25 0.00 1.00 0.00 0.25 0.75 0.75 0.50
0.50
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Totals: Ex-pharma-led firms (all 3 clusters) 13 0.46 0.15 0.46 0.08 0.15 0.62 0.69 0.31 0.38 0.31 0.38 0.69 0.54
Cluster 2 6 0.33 0.33 0.67 0.00 0.00 0.83 0.83 0.67 0.50 0.17 0.17 0.83 0.33
Cluster 3
3
0.67 0.00 0.00 0.33 0.33 1.00 0.00 0.00 0.33 0.00 0.33 0.67 1.00
Cluster 4 4 0.50 0.00 0.50 0.00 0.25 0.00 1.00 0.00 0.25 0.75 0.75 0.50 0.50
-------------------------------------------------------------------------------------------------------------------------------------------------Totals: Ex-pharma-led firms (all 3 clusters) 13 0.46 0.15 0.46 0.08 0.15 0.62 0.69 0.31 0.38 0.31 0.38 0.69 0.54
30
Four DBF Clusters
“One reason I called this company Integrated Genetics , instead of something else,
“According
a study
just
completed
bywith
the
Philadelphia-based
Institute
for
Scientific
Centocor’s
strategy
was
toAmphibious
be
“the
bridge
from
the
research
laboratory
to
“Much
of to
Amgen’s
success
in raising
capital
can
beacademic
attributed
toof
the
fact
that every
was
because
I wanted
a company
the
integrated
functions
research,
N
Y
Information
Genentech
leads
theworked
biotechnology
industry
for -theDavid
period
1981
through
June
the
health
supplier”
(Centocor
1982
Annual
Report)
scientific
founder?
oneestablished
of our(ISI),
senior
managers
had
forjust
large
corporations.
AsHousman,
a
result,
we had
development,
sales
andcare
marketing,
and
not
R&
D."
of
1992
in allGenetics
three categories
measured:
number
of publications,
greatest
number
the
organizational
discipline
of a
far greatest
bigger company,
withMIT,
salary
grades,
annual
Integrated
co-founder
and
professor
of biology,
Boston
Globe,
Decof
citations,
and greatest
of citations
per paper.
. . . Genentech
also
achieved
verywhat
high
“We
realized
itreviews,
was number
a lot
cheaper
to roam
academe
a
royalty
backa for
performance
monthly
reports,
and
budgetsand
thatpay
were
taken seriously.
All the
20,
1983
comparative ranking in citations per paper when compared
to five of America's best university
Just-offwe
developed
than
start our
own
research
facilities.”
(Founding
CEO Hubert
things
that
the
start-ups
rarely
do,
we
did;
to
us,
it
was
second
nature.”
– Gordon
Y
campus
departments of biological sciences. Genentech was second
only
toNthe Massachusetts
Institute
Schoemaker)
Binder,
Amgen’s
first
CFO
and
second
CEO
location? evaluated” (UCSF, Stanford,
of Technology's (MIT) Department of Biology of the five schools
Engaged
UC-Berkeley, and Princeton). -- Genentech
press release
Oct. 23, 1992
Y
N
in contract
research?
Cluster 1
Cluster 2
Cluster 3
Cluster 4
Differentiating attributes:
Differentiating attributes:
Differentiating attributes:
Differentiating attributes:
• Amphibious scientific
founders
• Emphasized publishing
scientific results
• Not reliant on SAB for
research direction
• VC in operational role
• Senior pharma exec.
recruited as CEO
• Noted scientists involved
as founders or on advisory
board, but publishing was
not emphasized
• Resembled spin-offs from
academic labs
• Focused on diagnostics
and other nontherapeutic applications
•Few research contracts
with large corporations
(i.e., “little r, big D”)
• Scientific breakthroughs
in-licensed from academy
• Deliberately assembled
business venture
• Repeat entrepreneur
among founders
• Pursued growth by
acquisition
• Located away from
campus
Biogen, California Biotech,
Cetus, Chiron, DNAX,
Genentech, Genetics Institute,
Immunex,
Molecular Genetics,
Repligen, Seragen,
Synergen , ZymoGenetics
Genzyme, Hybritech,
ImmunoGen, Integrated
Genetics, SIBIA, Xoma
Centocor, Codon,
Genetic Systems
Amgen, Cytogen, Genex,
Enzo
Four DBF Clusters
Y
Amphibious
scientific founder?
N
Just-offcampus
location?
Y
Y
Cluster 1
Engaged
in contract
research?
Cluster 2a
N
N
Cluster 2b
Cluster 2c
Differentiating attributes:
Differentiating attributes:
Differentiating attributes:
Differentiating attributes:
• Amphibious scientific
founders
• Emphasized publishing
scientific results
• Not reliant on SAB for
research direction
• VC in operational role
• Senior pharma exec.
recruited as CEO
• Noted scientists involved
as founders or on advisory
board, but publishing was
not emphasized
• Resembled spin-offs from
academic labs
• Focused on diagnostics
and other nontherapeutic applications
•Few research contracts
with large corporations
(i.e., “little r, big D”)
• Scientific breakthroughs
in-licensed from academy
• Deliberately assembled
business venture
• Repeat entrepreneur
among founders
• Pursued growth by
acquisition
• Located away from
campus
Biogen, California Biotech,
Cetus, Chiron, DNAX,
Genentech, Genetics Institute,
Immunex,
Molecular Genetics,
Repligen, Seragen,
Synergen , ZymoGenetics
Genzyme, Hybritech,
ImmunoGen, Integrated
Genetics, SIBIA, Xoma
Centocor, Codon,
Genetic Systems
Amgen, Cytogen, Genex,
Enzo
Publication quantity and quality by cluster*
Cluster 1
Cluster 2
Cluster 3
Cluster 4
Average
publications per
company
Average
publications per
company
Average
publications per
company
Average
publications per
company
584.54
185.83
148.67
266.25
Average citations per
publication
Average citations per
publication
Average citations per
publication
Average citations per
publication
66.63
29.12
45.35
44.76
Biogen, California Biotech,
Cetus, Chiron, DNAX,
Genentech, Genetics
Institute, Immunex,
Molecular Genetics,
Repligen, Seragen,
Synergen , ZymoGenetics
Genzyme, Hybritech,
ImmunoGen, Integrated
Genetics, SIBIA, Xoma
Centocor, Codon,
Genetic Systems
Amgen, Cytogen, Genex,
Enzo
* Publications tracked for 1st 10 years post-IPO. Citations as of Oct. 2010, self-cites excluded.
Self cites disproportionately boost Cluster 1’s citation counts. Source: ISI Web of Science
Consequences (in a narrow sense)
• Three recombinatorial DBF variants mixed and matched practices
borrowed from past experience
• One DBF variant was associated with amphibians who naively imported
practices of the invisible college into venture-financed startups
• Trespassing was the mother of invention: new scientific norms and new
models of funding improvised on the fly
• Similar financial events, very different meanings:
o
Acquisition by big pharma – security for recombination-based firms vs.
“end of Camelot” for transposition-based firms
o
IPO – liquidity event vs. “currency exchange” (scientific papers
converted into investment capital; helped retain junior scientists).
o
Publications – scientific leadership vs. “giving away crown jewels”
34
Impact of the DBF organizing models
• Scientific productivity of firms that were “in business to do science”
catalyzed changes in the conservative halls of the academy
• Commercial success of firms that were “in science to do business” has
resulted in a reordering of drug discovery in the pharmaceutical industry
• Result: blurred boundaries between university and commercial science
“The life sciences innovation system has ultimately replaced the
traditional divide between university science and
pharmaceutical innovation with a system that depends on
interdependent and collaborative knowledge development
spanning both public and private organizations.” (Cockburn and
Stern 2010)
35
Consequences (a broader view)
• Recombination and transposition can both give birth to new
organizational models
• Recombinatorial novelty is an interstitial phenomenon (Edelman et al.,
2001; Morrill 2008)
• Transposition represents the creation of new interstices, freighted with
generative potential
• Practices flowing across newly-created interstices catalyzed changes in
the conservative halls of the academy and industry, having effects well
beyond these organizations, opening up previously unconsidered
possibilities in different domains.
• A relational view of entrepreneurship - - amphibians as unintended
enablers of social invention; novelty as a consequence of traffic across
social worlds, not individual creativity or agency.
36
Feedback dynamics transform the academy and
industry
Academy:
• Embrace and celebration of academic entrepreneurship; remaking of
departments and schools to focus on translational research; adoption of
metrics to evince innovativeness; industry jobs no longer frowned on,
indeed encouraged.
Industry:
• Demise of insular internal R&D labs in Big Pharma; much greater
dependence on external sources of knowledge; creation of corporate
nonprofit institutes to do collaborative work; funding of postdocs;
encourage publishing
• Campus-like settings to attract the creative class
• Entrepreneur-in-residence programs at venture capital firms
Both:
• From discipline and department to projects
• Not a settlement but a continuing disruption, most notably in careers
and rewards
Not surprisingly, recombination proved a more robust business model in
the short term, but transposition had much more far-reaching long-term
consequences.
37
Implications
• In the short run, actors make relations. This is a story of
pragmatic search, where the tools of everyday practice were used in
unfamiliar circumstances, at a time when there was a green field.
• In the long run, relations make actors. In those settings where
science was repurposed, the tools and new interactions concatenated
to form new entities with effects that extended far beyond their initial
intentions.
• Some tools are more malleable than others; some regimes of worth
allow more ambiguity; some solutions to problems are less specific to
particular contexts. The principles and practices of open science both
enroll and mediate, undercutting some of the hierarchy of the
corporate world, and challenging some of the privileges formerly
reserved for the academic priesthood.
38