Amphibious Entrepreneurs and the Emergence of Organizational Forms* Walter W. Powell Kurt Sandholtz Stanford University 2012 This work appears in two formats,

Amphibious Entrepreneursand 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 & 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 yearsCompany Founding

YearLocation 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-BerkeleyBancroft 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, 23rd 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



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 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 existence.

SEC filings, Mergent reports, oral histories, newspapers, and books

9 (35%)

22

Attributes present in five or more of the DBFs



which code = 1

10. Encouraged scientific publication

Firm’s publication record was above the sample median on both quantity and quality measures.

ISI Web of Science (accessed electronically, October 2010) 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

CO.Cetus 1972 Bay Area (Emeryville) 81 1 1 1 1 0 1 1 0 1 0 1 0 1 92Genentech 1976 Bay Area (South SF) 80 1 1 0 1 0 1 1 1 0 0 0 0 0 09Enzo 1976 NYC 80 0 0 0 0 1 0 1 0 0 1 0 0 1 -Genex 1977 D.C. (Rockville, MD) 82 1 0 1 0 0 0 1 0 0 1 1 0 1 91Hybritech 1978 San Diego 81 0 1 0 0 0 1 1 1 0 0 0 1 1 85Biogen 1978 Boston 82 1 1 1 1 1 1 1 0 1 0 0 0 0 -MGI Pharma 1979 Minneapolis 82 1 1 0 0 1 0 1 0 0 0 0 0 1 08Seragen 1979 Boston (Hopkinton) 92 1 1 0 0 0 0 0 0 1 0 0 0 0 98Centocor 1979 Philadelphia 82 1 0 0 0 0 1 0 0 0 0 1 1 1 99DNAX 1980 Bay Area (Palo Alto) - 1 1 1 1 0 1 1 0 0 0 1 0 0 82Genetics Institute 1980 Boston (Cambridge) 86 1 1 0 1 0 1 1 0 1 0 0 1 0 97Genetic Systems Corp. 1980 Seattle 81 1 0 0 0 1 1 0 0 1 0 0 0 1 87Amgen 1980 Thousand Oaks 83 0 0 1 0 0 0 1 0 1 1 1 1 0 -Cytogen 1980 NJ (Princeton) 86 1 0 0 0 0 0 1 0 0 0 1 1 0 08Codon 1980 Bay Area (South SF) - 0 0 0 0 0 1 0 0 0 0 0 1 1 90Integrated Genetics 1981 Boston (Framingham) 83 1 1 1 0 0 0 1 1 1 0 0 1 1 90SIBIA 1981 San Diego 96 0 0 1 0 0 1 1 0 1 0 0 0 0 99Xoma 1981 Bay Area (Berkeley) 86 0 0 0 0 0 1 1 0 1 0 0 1 0 -Chiron 1981 Bay Area (Emeryville) 83 1 1 0 1 1 1 1 0 0 0 0 0 0 06Immunex 1981 Seattle 83 1 0 0 1 1 1 1 0 0 0 0 0 0 01Repligen 1981 Boston (Cambridge) 86 1 1 0 1 1 1 1 0 1 1 0 0 1 -Scios 1981 Bay Area (Mt. View) 83 1 1 0 1 0 0 1 0 1 1 0 0 0 03Synergen 1981 Boulder, CO 86 1 1 0 1 1 1 1 0 0 0 0 0 1 94ZymoGenetics 1981 Seattle - 1 1 0 0 1 1 1 0 0 0 0 0 0 88Genzyme 1981 Boston 86 0 0 1 0 0 1 0 1 0 1 1 1 0 -Immunogen 1981 Boston (Cambridge) 89 1 0 1 0 0 1 1 1 0 0 0 1 0 -

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 attributesE-I ratio =

(Krackhardt and Stern, 1988)

0

0.2

0.4

0.6

0.8

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Number of Clusters

“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.

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Branches of the DBF Tree

30

Table 5a: Aggregate Attribute Profiles for the Two Parent Clusters

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

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

Table 5b: Aggregate Attribute Profiles for the Three Ex-Pharma-Led Clusters

-------------------------------------------------------------------------------------------------------------------------------------------------- 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

Table 5a: Aggregate Attribute Profiles for the Two Parent Clusters

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

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

Table 5b: Aggregate Attribute Profiles for the Three Ex-Pharma-Led Clusters

-------------------------------------------------------------------------------------------------------------------------------------------------- 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

“In business to do science”

“In science to do business”

Engaged in contractresearch?

Just-off-campuslocation?

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


• 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


• Deliberately assembled business venture

• Repeat entrepreneur among founders

• Pursued growth by acquisition

• Located away from campus

Amgen, Cytogen, Genex, Enzo

NY

Cluster 1


• 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

NY

NY

“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 contractresearch?

Just-off-campuslocation?

Four DBF Clusters

Amphibious scientific founder?

Cluster 2a


• 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


Cluster 2b


• 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


Cluster 2c


• Deliberately assembled business venture

• Repeat entrepreneur among founders

• Pursued growth by acquisition

• Located away from campus


NY

Cluster 1


• Amphibious scientific founders

• Emphasized publishing scientific results

• Not reliant on SAB for research direction


NY

NY

Publication quantity and quality by cluster*

Cluster 2

Average publications per

company

185.83

Average citations per publication

29.12


Cluster 3


company

148.67


45.35


Cluster 4


company

266.25


44.76


Cluster 1


company

584.54


66.63


* 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

• 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 rewardsNot 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.

Documents

Amphibious Entrepreneurs and the Emergence of Organizational Forms* Walter W. Powell Kurt Sandholtz Stanford University 2012 This work appears in two formats,