and the Emergence of Organizational Forms*

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23 Οκτ 2013 (πριν από 3 χρόνια και 11 μήνες)

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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


“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

Fertile ground for studying emergence of
new organizational forms

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 & 1
st

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

Founding

Year

Location

Currently

Cetus

1972

Berkeley, CA

Acquired

by Chiron (1991)

Enzo Biochem

1976

New York City, NY

Independent

Genentech

1976

South San Francisco, CA

Subsidiary of
Roche (2010)

Genex

1977

Rockville, MD

Acquired

by
Enzon

(1991)

Biogen

1978

Zurich,

and
Cambridge
, MA

Merged with Idec to form
Biogen

Idec (2003)

Hybritech

1978

San Diego, CA

Acquired

by Eli Lilly (1986) then Beckman Coulter (1995)

Centocor

1979

Philadelphia, PA

Subsidiary of Johnson &
Johnson (1999)

Molecular

Genetics

1979

Minneapolis, MN

Acquired

by Eisai (2008)

Seragen

1979

Hopkinton, MA

Acquired by

Ligand

(1998)

Amgen

1980

Thousand Oaks, CA

Independent

Codon

1980

South San Francisco, CA

Acquired by
Berlex

(U.S. arm of Schering AG) (1990)

Cytogen

1980

Princeton, NJ

Acquired by EUSA (2008)

DNAX

1980

Palo Alto, CA

Acquired by Schering
-
Plough (1982)

Genetic Systems Corp.

1980

Seattle. WA

Acquired by Bristol
-
Meyers (1987)

Genetics Institute

1980

Boston, MA

Acquired

by
Wyeth (
1996), which Pfizer acquired (2009)

Chiron

1981

Emeryville, CA

Acquired

by Novartis (2006)

Genzyme

1981

Boston, MA

Subsidiary of
Sanofi
-
Aventis (2011)

Immunex

1981

Seattle, WA

Acquired by Amgen (2002)

ImmunoGen

1981

Cambridge, MA

Independent

Integrated Genetics

1981

Framingham, MA

Acquired by
Genzyme

(1989)

Repligen

1981

Cambridge, MA

Independent

California Biotechnology

1981

Mountain View, CA

Subsidiary of Johnson & Johnson (2003)

SIBIA

1981

San Diego, CA

Acquired by Merck (1999)

Synergen

1981

Boulder, CO

Acquired by Amgen (1994)

Xoma

1981

Berkeley, CA

Independent

ZymoGenetics

1981

Seattle, WA

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

# of pages
analyzed

Companies included

Regional Oral History Office,
UC
-
Berkeley

Bancroft Library

First
-
person accounts of scientists, venture capitalists,
executives, and employees of the earliest biotech
firms

2,000+

Amgen, Genentech,
Centocor, Chiron, Cetus,
Hybritech, DNAX

Lexis/Nexis U.S. newspaper
database, ABI Inform

Journalist accounts of the companies and their
founders

950+

All

American Men and Women of
Science

Brief biographies of notable scientists

18

N/A

Mergent Business Profiles
(formerly Moody’s)

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
of the earliest biotech ventures

1,500+

All

Primary data

Semi
-
structured telephone interviews

200+

Codon
,
Genex
,
Genzyme
,
Immunex
, Integrated
Genetics,
ZymoGenetics


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

No. (%) of
firms for
which
code = 1

1
.
Research contracts
with large
corporations

Research contracts cited as a critical source of
operating revenue.

Mergent

reports,
BioScan

directory, SEC filings,
newspapers, and books

21
(81%)

2.
Noted scientist(s)

At least one founder listed in
American Men &
Women of Science
1

American Men & Women of
Science
, 23
rd

ed. , 2007.

19
(73%)

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

18
(69%)

4
.
Amphibious
scientist(s)

At least one founder was a company officer and
(a) occupied an academic position simultaneously,
or (b) returned to full
-
time academic research later

Oral histories, newspapers,
books,
American Men & Women
of Science
, and SEC filings.

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
diagno獴i捳c va捣cne猬 or other non
J
therapeuti挠
products
.


Mergent

reports, SEC filings,
newspapers, oral histories

11
(42%)

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

11
(42%)

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

10
(38%)

8
.
All
-
Star Scientific
Advisory Board

Firm (a) had a scientific advisory board (SAB)
separate from founders, and (b) this SAB included
at least one renowned scientist

SEC filings, oral histories,
newspapers, and books.


9
(35%)

9
.
Scientist in charge

Academic scientist served as
president

or

CEO

at
some point during first three years of company’s
exi獴en捥.

pbC filing猬
Mergent

reports,
oral histories, newspapers, and
books


9
(35%)

22

Attributes present in
five or more of
the
DBFs

Attribute

Basis for code = 1

Sources

No. (%) of
firms for
which
code = 1

10.
Encouraged scientific
publication

Firm’s publication record was above the
獡mple median on both quantity and quality
mea獵res
.

fpf teb of p捩en捥 Ea捣c獳sd
ele捴roni捡llyI l捴ober OM1MF


8 (31%)

11. Prior
entrepreneurial
experience

At least one founder had been involved in a
prior start
-
up.

Oral histories, SEC filings,
newspapers


7
(27%)

12.
Growth through
acquisition

Within the
five
years following its founding,
the firm made at least one acquisition .

Mergent
reports, newspapers,
SEC filings


6
(26%)

13.
Venture capitalist served
in operational role

Venture capitalist (a) occupied executive
role, or (b) actively intervened in day
-
to
-
day
operations.

Oral histories, newspapers,
books


5
(19%)

23

24

25

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

26

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)


27

Textual
dendrogram

(aka “icicle diagram”)

We selected four clusters as the optimal level of agglomeration

Figure 3: Selecting the optimal number of clusters


(# of attributes shared with firms outside the cluster


# of attributes shared with firms within the cluster)

# total shared attributes

E
-
I ratio =

(Krackhardt and Stern, 1988)


“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.

The Dedicated

Biotech Firm

1

2

3

4

Branches of the DBF Tree

30

“In business to do science”

“In science to do
business”

Engaged
in contract

research?

Just
-
off
-

campus

location?

Four DBF Clusters

Amphibious
scientific founder?

Cluster 2


Differentiating attributes:




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


Genzyme
,
Hybritech
,

ImmunoGen
, Integrated
Genetics, SIBIA,
Xoma


Cluster 3


Differentiating attributes:




Focused on diagnostics


and other non
-


therapeutic applications


Few research contracts


with large corporations


(i.e., “little r, big D”)



Scientific breakthroughs


in
-
licensed from academy


Centocor
,
Codon
,

Genetic Systems

Cluster 4


Differentiating attributes:




Deliberately assembled


business venture



Repeat entrepreneur


among founders



Pursued growth by


acquisition



Located away from


campus



Amgen,
Cytogen
,
Genex
,

Enzo


N

Y

Cluster 1


Differentiating attributes:




Amphibious scientific


founders



Emphasized publishing


scientific results



Not reliant on SAB for


research direction


Biogen
, California Biotech,

Cetus
, Chiron, DNAX,

Genentech, Genetics Institute,
Immunex
,

Molecular Genetics,

Repligen
,
Seragen
,

Synergen

,
ZymoGenetics



N

Y

N

Y

“One reason I called this company Integrated Genetics , instead of something else,
was because I wanted a company with the integrated functions of research,
development, sales and marketing, and not just R & D."
--

David Housman,
Integrated Genetics co
-
founder and professor of biology, MIT, Boston Globe, Dec
20, 1983


“According to a study just completed by the Philadelphia
-
based Institute for Scientific
Information (ISI), Genentech leads the biotechnology industry for the period 1981 through June
of 1992 in all three categories measured: greatest number of publications, greatest number of
citations, and greatest number of citations per paper. . . . Genentech also achieved a very high
comparative ranking in citations per paper when compared to five of America's best university
departments of biological sciences. Genentech was second only to the Massachusetts Institute
of Technology's (MIT) Department of Biology of the five schools evaluated” (UCSF, Stanford,
UC
-
Berkeley, and Princeton).
--

Genentech press release Oct. 23, 1992


“Much of Amgen’s success in raising capital can be attributed to the fact that every
one of our senior managers had worked for large corporations. As a result, we had
the organizational discipline of a far bigger company, with salary grades, annual
performance reviews, monthly reports, and budgets that were taken seriously. All the
things that the start
-
ups rarely do, we did; to us, it was second nature.”



Gordon
Binder, Amgen’s first CFO and second CEO

Centocor’s

strategy was to be “the bridge from the academic research laboratory to
the established health care supplier”
(
Centocor

1982 Annual Report)


“We realized it was a lot cheaper to roam academe and pay a royalty back for what
we developed than start our own research facilities.”
(Founding CEO Hubert
Schoemaker
)

Engaged
in contract

research?

Just
-
off
-

campus

location?

Four DBF Clusters

Amphibious
scientific founder?

Cluster 2a


Differentiating attributes:




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


Genzyme
,
Hybritech
,

ImmunoGen
, Integrated
Genetics, SIBIA,
Xoma


Cluster 2b


Differentiating attributes:




Focused on diagnostics


and other non
-


therapeutic applications


Few research contracts


with large corporations


(i.e., “little r, big D”)



Scientific breakthroughs


in
-
licensed from academy


Centocor
,
Codon
,

Genetic Systems

Cluster 2c


Differentiating attributes:




Deliberately assembled


business venture



Repeat entrepreneur


among founders



Pursued growth by


acquisition



Located away from


campus



Amgen,
Cytogen
,
Genex
,

Enzo


N

Y

Cluster 1


Differentiating attributes:




Amphibious scientific


founders



Emphasized publishing


scientific results



Not reliant on SAB for


research direction


Biogen
, California Biotech,

Cetus
, Chiron, DNAX,

Genentech, Genetics Institute,
Immunex
,

Molecular Genetics,

Repligen
,
Seragen
,

Synergen

,
ZymoGenetics



N

Y

N

Y

Publication quantity and quality by cluster*

Cluster 2



Average
publications per
company


185.83


Average citations per
publication


29.12






Genzyme
,
Hybritech
,

ImmunoGen
, Integrated
Genetics, SIBIA,
Xoma


Cluster 3



Average
publications per
company


148.67


Average citations per
publication


45.35







Centocor
,
Codon
,

Genetic Systems

Cluster 4



Average
publications per
company


266.25


Average citations per
publication


44.76







Amgen,
Cytogen
,
Genex
,

Enzo


Cluster 1



Average
publications per
company


584.54


Average citations per
publication


66.63



Biogen
, California Biotech,

Cetus
, Chiron, DNAX,

Genentech, Genetics
Institute,
Immunex
,

Molecular Genetics,

Repligen
,
Seragen
,

Synergen

,
ZymoGenetics



* Publications tracked for 1
st

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


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

Consequences (in a narrow sense)

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

37

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
.



38

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.