Not Your Stepping Stone: Collaboration and the Dynamics of Industry Evolution in Biotechnology


Description of Biotechnology Agreements



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Description of Biotechnology Agreements

Type of Tie

Typical Kinds of Partners




R&D: Biotech firm develops research program with another organization for a specific target.
Finance: Partner invests funds in a BF,

or BF invests funds (and usually

scientific expertise) in a partner.

Other biotechs, pharmaceutical corps., universities, research institutes.



Venture capital firms, larger biotech companies, pharmaceutical corps.







Licensing: BF either licenses its intellectual property (IP) to another party, or acquires license to others’ IP.

Universities, BFs, pharmaceuticals.







Clinical Trials/Evaluation: BF has partner conduct trials on human subjects for FDA approval.

Research hospitals, organizations specializing in clinical trials.







Commercialization: BF contracts with partner to manufacture and market its product, or BF agrees to supply product to a distributor for sales.

Large pharmaceutical or chemical corps., larger BFs.








Complex: a tie between a BF and another party that involves multiple activities (i.e., R&D and marketing)


Any partner (except venture capital).

Table 2: Descriptive Statistics for Biotechnology Firms





Mean

Standard Deviation

Maximum

N firm-years*

Size (employees)

153.52

435.42

7500

2946

Age (years)

7.7575

5.7670

42

4144
















Number of ties:













R&D

1.8727

2.9779

25

4178

Finance

2.7252

4.1790

52

4178

Licensing

1.5785

3.1784

43

4178

Evaluation

0.0764

0.3983

6

4178

Commercial

1.1309

2.5444

23

4178

Complex

1.1168

2.4496

32

4178

Total

8.5005

10.5118

91

4178
















Number of types

2.4050

1.5371

6

4178
















Number of ties per partner

1.1501

.2821

5

3864
















Earnings ($M)

-48.0

32.33

879.4

1061






























* The differences in the number of firm years reflect missing data for some companies with respect to size and/or age. With respect to the number of ties, a small number of firms have no ties of any kind. The earnings data are based on 154 publicly traded firms in the United States and cover those years for which financial reports are available.

Table 3: Effects of firm growth on depth of collaboration.*






Dependent Variable at time t




Overall number of ties

Number of types of tie activity

Number of complex ties

Size at time t-1

.6160****

(.0392)


.0294***

(.0061)


.1113****

(.0119)














Within-firm r-square

.10

.03

.09













Full r-square

.83

.69

.84













N firm-years

2349

2349

2349













N firms

407

407

407

All models include both firm and year fixed effects.

Significance levels: ***=p<.001; ****=p<.0001
* Only firms with at least one tie at time t-1 are included in these analyses.

Table 4: Effects of aging on scope (initial use of each type) of collaborative activity.*







Number of ties of specific type of tie activity at time t




R&D

Finance

Licensing

Evaluation

Commercial

Complex

Age at time t-1

.0311****

(.0048)


.0267****

(.0050)


.0288****

(.0037)


.0180*

(.0012)


.0246****

(.0030)


.0281****

(.0038)























Within-firm r-square

.03

.02

.04

.01

.03

.03






















Full r-square

.35

.32

.33

.24

.28

.32






















N firm-years

1482

1363

1658

3220

2136

1839






















N firms

319

291

327

439

374

360

All models include fixed firm and year effects.

Significance levels: *=p<.05; ****=p<.0001.
* Only firms without specific type at time t-1, but with at least one other type at time t-1are included in these analyses.

Table 5: Effects of aging on reach (number of kinds of partners) for each type of collaborative activity.*







Number of kinds of partners by specific type of tie activity at time t




R&D

Finance

Licensing

Evaluation

Commercial

Complex

Age at time t-1

.0530**

(.0107)


.0715****

(.0106)


.0471****

(.0096)


.0260*

(.0107)


.0502***

(.0139)


.0047

(.0038)























Within-firm r-square

.03

.02

.02

.01

.01

.00






















Full r-square

.55

.70

.66

.61

.61

.57






















N firm-years

1570

2239

1495

1616

1986

1140






















N firms

306

381

295

312

358

244

All models include fixed firm and year effects.

Significance levels: *=p<.05; **=p<.01;***=p<.001;****=p<.0001.
* Only firms with at least kind of partner for specific type at time t-1are included in these analyses.

Table 6: Effects of positive earnings on reinvestment in collaborative R&D.*







Number of R&D alliances at time t

Positive earnings at time t-1

2.0500****

(.5038)








Within-firm r-square

.03







Full r-square

.73







N firm-years

716







N firms

133

All models include fixed firm and year effects.



Significance levels: ****=p<.0001
* Only firms with at least one R&D alliance at time t-1are included in these analyses.


1 There is clearly an important difference between formal and informal organizational linkages. Contractual relationships are crafted with considerable care and typically entail milestones or covenants dictating certain types of expected performance. Informal linkages more typically involve unwritten understandings, quid pro quos, and tacit agreements. Moreover, informal relationships are often entangled in ongoing friendships among employees of organizations. Such interpersonal ties are often less calculative and voluntaristic than formal ties. Our focus here is on direct organization to organization relationships that involve the transfer of resources and/or information. In companion work, we are collecting “founding stories” for all the firms in our database, and it is clear that at the point of organizational founding, the ties linking organizations are more often person-to-person linkages, and that formal affiliations come later.

2 Obviously, success is a relative term. None of these firms are hugely successful in comparison to software giant Microsoft or a computer firm like Dell. But success is used multi-dimensionally here; these firms are growing in size, surviving, and, in some cases, generating sufficient revenues for reinvestment.

3 We thank Steve Klepper for first emphasizing this point to us.

4 An important question is just how much diversity can an organization sustain. In a recent paper, we found declining returns to network diversity and experience after an organization crossed a threshold of connected ness. Once centrally positioned, with a portfolio of partners, there were scant returns to performance from adding more collaborators (Powell et al, 1999).

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