Organisational Aligment in Knowledge Based Industries

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Science, Technology & Innovation Studies Vol. 2 (March 2006)

ISSN: 1861-3675

STIStudieswww.sti-studies.de

Institutions Matter but Organisational Alignment in Knowledge-Based Industries1Petra Ahrweiler2(University of Hamburg)Nigel Gilbert (University of Surrey)Andreas Pyka (University of Augsburg)received 21 October 2005, received in revised form 6 February 2006, accepted 13 February2006

AbstractA comparison of the current structures and dynamics of UK and German biotech-nology-based industries reveals a striking convergence of industrial organisationsand innovation directions in both countries. This counteracts propositions fromtheoretical frameworks such as the varieties-of-capitalism hypothesis and the na-tional innovation systems approach which suggest substantial differences betweenthe industrial structures of the countries due to differing institutional frameworks.

In this paper, we question these approaches and show that the observed structuralalignment can be explained by the network organisation of research and produc-tion in knowledge-based industries.

1 This work was partially supported by the German DAAD and the British Council within athree-year research project, Innovation networks in biotechnology-based industries. Wethank our referees for their valuable comments.2 Corresponding author: [email protected]


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4 STI Studies 2006: 3-18

1 IntroductionIn knowledge-based economies themechanisms of knowledge creationand utilisation are changing. Industrial

economics and new innovation theoryconsider the increasing complexity ofknowledge, the accelerating pace ofthe creation of knowledge, and theshortening of industry life cycles to beresponsible for the rising importanceof innovation networks. Knowledge-intensive industries such as IT andbiotechnology have already undergonestructural changes towards thesecollective modes of knowledge produc-tion and application. Such networks

seem to be an important component ofthe emerging knowledge-based econo-mies in which knowledge is crucial foreconomic growth and competitiveness.

For some authors, the omni-presentnetworks even "constitute the newsocial morphology of our societies(Castells 2000: 500) which are accord-ingly labelled as network societies.However, this suggests that networkformation follows some global and

universal trend affecting, unifying, andarranging all parts of society in "vari-able geometries (Castells 2000) whereheterogeneity and diversity is sacri-ficed for a single over-powering pat-tern of development. As we havementioned elsewhere (Pyka/Ahrweiler2004), this view does not take intoaccount the complex reality of eco-nomic phenomena deeply intertwined

with cognitive, institutional, organisa-tional and political aspects, i.e. a world

of institutional variety, historicity andpath-dependence.

In this article, we argue that the rela-tion between knowledge, networksand heterogeneous institutionalframeworks is much more complicatedthan acknowledged by the protago-nists of "globalisation or the so-callednetwork society. Network formation is,on the one hand, closely linked to theknowledge-intensity of a few indus-

tries and, on the other, not substitut-ing but complementing the influence

of institutional frameworks in order toco-ordinate economic action. The nextparagraphs will work out these propo-sitions in more detail.

2 Institutions matter"At the start of the twenty-first centurythe role of institutions and the condi-tions for institutional change are at thecore of the economic debate inEurope (Amable 2003: 1). Neo-institutional approaches (e.g. North1981; Olson 1984) claim that institu-tions shape the structure and dynam-ics of societies: they emphasise that

each national society has developed acontext and path dependent institu-tional infrastructure (politics, law,economy, culture). Economic actionsare strongly influenced by these spe-cific infrastructures, which accordinglylead to different national industrialstructures and performances.

2.1 Varieties of CapitalismAlthough, as the sociological "varieties

of capitalism (VoC) thesis states,national industries do look different,each formation can offer a particularcomparative institutional advantageenabling economic success within thedifferent national frameworks(Hall/Soskice 2001). VoC studies (e.g.Petit/Amable 2001; Amable 2003)maintain that UK and Germany havecompletely different institutionalinfrastructures: while the UK is la-belled as a "liberal market economy,

Germany is deemed to be a "co-ordinated market economy. Thedifferences are traced back to nationalregulations of labour and corporatelaw, to institutional differences incompetence development and tech-nology transfer, and to differences infinancial systems. Considering these

wide-ranging differences in the institu-tional frameworks in UK and Germany,summarised in Table 1, it seems rea-sonable to expect substantial differ-

ences in the organisation of theirnational industries. Generally, Ger-


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Ahrweiler/Gilbert/Pyka: Institutions matter but ... 5

many is considered to be burdenedwith an "old institutional infrastruc-ture compared to the UK. Germanindustrial society contains nationallyunified institutions such as largeindustrial corporations, bureaucratic

organisations, professional manage-ment, dual professional educationsystems, social security systems,labour unions and formal regulation,hierarchical co-ordination and ataylorised structure of work. As Hei-denreich states: "There are no signsthat Germany and other ContinentalEuropean economies will follow theBritish lead and will get rid of theirinstitutional structures developed overdecades. These particular institutionalsettings cannot be dismissed as the old

garbage of industrial society (Heiden-reich/Toepsch 1998: 14; own transla-tion).

Compared to the UK, some require-ments of modern knowledge societies(see e.g. OECD 1996) are less likely tobe fulfilled by the institutional infra-structure in Germany. Focussing onknowledge creation, knowledge trans-fer and the commercialisation of

knowledge, knowledge-based econo-mies require permanent access across

borders between nations and firms asa pre-condition for economic action.This is needed to achieve, for example,quick commercialisation of scientificresults from basic research, easyaccess to finance for risk-intensive

projects, the motivation of scientificentrepreneurs, and the availability ofparticipative management skills. Tosatisfy project requirements, highly-qualified and flexible staff have to beable to migrate without the hindrancesresulting from firm and educationbarriers (for German difficulties in thisarea see Soskice 1997, EPOHITE 2000).Table 1 summarises the issues.

The VoC literature would seem to

predict that innovative industries,characterised by a high researchintensity, extensive capital needs, andhigh risk and uncertainty, would facedifficult development conditions inGermany and would be far less devel-oped than the UK's and that this willstay as it is because institutionschange slowly, if at all. Compared tothe UK, the comparative advantage ofGermany would be best maintained byconcentrating its strength in the con-

ventional industrial sectors.

Table 1- National institutional frameworks in Germany and the UKGermany UK

Labour Lawregulative (coordinated sys-tem of wage bargaining;

constraints on employeedismissals)

liberal (decentralised wagebargaining; fewer barriers to

employee turnover)

Company law stakeholder system (two tierboard system plus codetermi-nation rights for employees)

shareholder system (minimallegal constraints on companyorganisation)

Skill formationand technol-ogy transfer

organised apprenticeshipsystem with substantial in-volvement from industry.Close links between industryand technical universities indesigning curriculum andresearch

no formal apprenticeshipsystem for vocational skills.Links between universitiesand firms almost exclusivelylimited to R&D activities andR&D personnel

Financialsystemprimarily bank-based withclose links to stakeholdersystem of corporate govern-ance; no hostile market forcorporate control

primarily capital marketsystem, closely linked tomarket for corporate controland financial ownership andcontrol of firms

Source: Casper/Kettler 2001: 14


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2.2 National Innovation SystemsThe notion of "national innovationsystems (NIS) was introduced toinnovation research in the 1980s to

emphasise the important role playedby the specific national institutionalsettings and non-economic actors forthe innovative performance of aneconomic system. According to Beije(1998), an innovation system "can bedefined as a group of private firms,public research institutes, and severalof the facilitators of innovation, who ininteraction promote the creation ofone or a number of technologicalinnovations [within a framework of]

institutions which promote or facilitatethe diffusion or application of thesetechnological innovations" (Beije 1998:256).

The NIS approach (Lundvall 1992;Nelson 1993) focuses on actors andtheir interactions embedded in anational institutional infrastructure.Innovation and innovation-basedeconomic performance is organiseddifferently across national borders.

Like the VoC literature, the NIS ap-proach concentrates on "the systemicaspects of innovation [and of] diffusionand the relationship to social, institu-tional and political factors (Fagerberg2003: 141). Lundvall, additionally,contributes an emphasis on compe-tence building and the learning capa-bilities of individuals, organisations,regions and nations (Lund-

vall/Tomlinson 2002: 218, see theAalborg-Freeman approach of NIS

(Lundvall 1992)). Differentiating,elaborating and complementing theNIS concept, recent research targetssectoral systems of innovation(Malerba 2002), technological systems,regional innovation systems and localtechnology clusters (Feldman et al.2005).

The NIS approach suggests a diagnosissimilar to that of the VoC studies3.

3 For a detailed comparison of recent NISand VoC approaches see Werle 2005.

Balzat summarises the results of the2003 innovation report of the GermanMinistry of Economics: "On the nega-tive side, Germany has problems tocatch up with the USA and with theNordic European countries in thedevelopment and dissemination oftechnologies such as ICT and biotech-nology. A rapid reversal of the German"backwardness in this high technol-ogy field seems rather unlikely forthree main reasons. First, Germanyhas lost ground in the level of ICTexpenditure within the last decade.Second, the German labor market fallsshort of highly qualified workers and

technical engineers. Third, the industryin the Eastern part of Germany is stillfar behind the West German in produc-tivity levels and in the innovativenessof business firms (Balzat 2004: 115).In order to compare different nationalinstitutional frameworks of innovation,Balzat constructed a NIS model con-taining 54 indicators that operational-ise 19 sub-blocks of six main NIScomponents (knowledge base, financ-ing conditions, internationalisation,

innovation and learning incentives,innovative efforts, framework condi-tions)4. Figure 1 shows a simplified

version of his NIS performance model.

Using this set of indicators with theoperationalisation mentioned in Balzat(2004), the differences between thenational innovation systems of UK andGermany can be visualised as in Figure2. The different designs of the nationalinnovation systems in UK and Ger-

many can easily be seen. Whereas theGerman system performs better in thedimensions of innovative efforts,knowledge base and internationalisa-tion, the UK system shows advantages

with respect to financing conditions,.

4 For a discussion of parameter construc-tion, indicator building and interpretationof results, see Balzat 2004: 156-218.


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learning incentives and frameworkconditions, all features important forthe evolution of entrepreneurial indus-tries. Summarising, both the VOC andthe NIS approaches leave us with thesame set of research hypotheses aboutGermany's and the UK's knowledge-based innovation. For the UK, as theexample par excellence of a liberal

market economy (Amable 2003), weexpect entrepreneurial knowledge-

intensive industries supported byprogressive venture capital focussingon blockbusters following radicalproduct innovation strategies. ForGermany, as the example par excel-

lence for a co-ordinated market econ-omy (Amable 2003), we expect,mutatis

mutandis, industries with a small rateof entry, conservative venture capital if

any, and focussing on incrementalinnovation, i.e. process innovation.

Figure 1: Indicators for comparing different institutional frameworks(Source: Balzat 2004: 158)

Employment-related factors

Private R&D spending

Public R&D spending

Gross domestic R&D spending

Macroeconomic framework

R&D incentives

Diffusion of ICT

Tax burden

Present inventiveness(scientific success)

Future inventiveness(real measures)

Future inventiveness(monetary measures)

VC availability

Financial market costs

Financial market institutions

Capital market openness

Science and education

FDI inflows

High-tech trade

Innovation and learning

incentives

Innovative efforts

Framework conditions

Knowledge base

Financing conditions

Internationalization

NIS

Present inventiveness( ersonal)


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3 Institutions matter butThere seems to be general agreementabout the varying institutional frame-

works of UK and Germany. For themanufacturing industries, in the lasttwenty years this has lead to divergentdevelopments in Germany and Britain(e.g. machine tools and car manufac-turing, for an overview comparingindustrial structures in both countriescf. Matraves 1997). As the varieties ofcapitalism hypothesis states, this isalso and even especially expectedfor the knowledge-intensive industries.

In the following sections we shallconsider the so-called "red biotech-nology sector, which covers pharma-ceutical applications of molecularbiology, also often referred to as

"biopharmaceuticals. Contrary to theexpectations we derived from the VoCand NIS approaches, we shall observestriking structural and proceduralsimilarities. The biopharmaceuticalindustries of the two countries havebecome more and more similar both intheir focus on product and processtechnologies, and in the make-up oftheir industrial organisations (clusters,start-ups, spin-offs etc.).

3.1 Empirical evidence: the biophar-maceutical sectorIn this section we will present somestatistics describing the bio-pharmaceutical industries in theUnited Kingdom (UK) and in Germany(D).5

Figure 3 demonstrates market sizesand their growth, measured by thepercentage of GDP of pharmaceuticalsales. The markets are of similar sizein both economies and the trendsshow the same direction.

Figure 4 compares the markets forpharmaceuticals in UK and D by de-picting the market shares of noveltiesintroduced by national companies

within the last 5 years. Again the

development and the overall sizes arerather similar for Germany and theUnited Kingdom. However, the Germanfigure is slightly above the Britishfigure over the whole time period.

5 Except that, in some cases, the data wewould like to have presented is not avail-able and so we have used data about thepharmaceutical sector as a whole. A con-

siderable part of the new technologies inthe pharmaceutical sector are based onmethods from biotechnology.

Figure 2 - Comparing NIS components of UK and GermanyInnovative efforts

Knowledge base

Financing conditions

Innovation and learning incentives

Framework conditions

Internationalization

GermanyUnited Kingdom (Source: Balzat 2004)


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Figure 5 - International comparison of the number of core biotech firms

0

200

400

600

800

1000

1200

1400

1600

U.S.

Canada

Germany UK

France

Australia

SwedenIsrael

Switzerland

TheNetherlands

Finland

Denmark

Number of biotechnology companies (public and private companies)

Source. Ernst & Young, 2004

Figure 4 - Share of innovations in the pharmaceutical market in UKand D

0

5

10

15

20

25

30

1998 1999 2000 2001 2002 2003

Germany UK

New pharmaceuticals launched within the las t 5 years

(percentage by value of the national market)

Source: PICTF, 2004

Figure 3 - Market Size in UK and D

0

0,2

0,4

0,6

0,8

1

1,2

1998 1999 2000 2001 2002 2003

Germany UK

Pharmaceutical Sales as Percentage of GDP

Source: PICTF, 2004


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Figure 5 describes the size of thebiotech firm population. For 2003,Ernst & Young (2004) records a rathersimilar number of firms in the twonations. If we look at the developmentof the firm population over time (Fig-ure 6) we see that the number ofGerman biotech firms has increased

continuously and since 1999 is evenslightly greater than the number in theUK in the same years.

If we examine the number of venturecapital (VC) cooperations in bothcountries shown in figure 7, a corre-sponding similarity can be observed.The number of deals in Germany is

slightly above those in the UnitedKingdom, whereas the amount ofmoney involved in transactions is

higher in the United Kingdom thanGermany.

These findings seem contrary to whatwould be expected from the VoCliterature concerning a comparisonbetween the German and the UKbiotech industries. A considerable

entry of firms was only expected forthe UK; for Germany, a similar devel-opment was not expected at all. Ofcourse, a major reason for the prolif-eration of biotech firms in Germanymust be the huge efforts to supportentrepreneurial behaviour comingfrom technology policy.

Figure 7- VC cooperations in UK and D

0

50

100

150

200

250

300

UK Germanyamount raised (m) number of deals

Source: Ernst & Young, 2004

Figure 6 - Development of private biotech firms in UK and D

0

100

200

300

400

1998 1999 2000 2001 2002 2003

Germany UK

Number of private biotechnology companies

Source: Ernst & Young, 2004


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3.2 Empirical evidence: firm strategiesThe VoC studies also suggested thatGerman firms would pursue innova-tion strategies that excluded product

innovation, e.g. the development oftherapeutics, expecting this country tostick with process innovation. Instead,data from 2004 show that more thanhalf (56%) of the German biotechcompanies consider the developmentof therapeutics as their main area ofaction. A more detailed comparisonfrom 2002 also points in this direction:

In 2004, 32 firms in each country weredeveloping therapeutics that hadalready reached the clinical phase.Managers from UK and Germanyreported similar reasons for theirstrategic decisions (Ernst & Young2004). Chances, possibilities and risksare estimated in similar ways by man-agers in the two countries. A compari-son of the number of new drugs intro-duced to the market in both countries

(figure 8) shows that also the finaloutcome in UK and Germany is rela-tively similar.

Figure 9 shows German and BritishR&D efforts in an international com-parison. The relative position of Ger-many slightly worsens in the timeperiod shown, but both nations have

very similar shares of the global total.

In Figure 10 we see the percentage ofall pharmaceutical patents awarded toa country divided by the percentage ofR&D efforts of its pharmaceutical

industry, a measure of R&D efficiency.The efficiency for UK is higher over thefour periods investigated. However,again the trend is in the same directionfor both countries.

Figure 11 shows the time elapsingbetween the first application in anymarket and the launch in the particularnational market in Germany and UK.The three main reasons for delay arecompany strategy (when to apply,

when to launch), the length of theregulatory process, and the length ofthe pricing and reimbursement proc-ess. The time between approval andlaunch in the national market is

somewhat shorter in Germany com-pared to the United Kingdom. How-ever, in Germany it takes considerablylonger if the time span between thefirst application and the application tothe national market is considered. Theregulatory conditions in Germany areaccordingly less favourable in thissingle respect.

This section has clearly indicated theoverall structural similarity of UK's and

Germany's biopharmaceutical indus-tries. The similarity is also visible fromother countries: the foreign directinvestment (FDI) inflows show thatGermany, a 'co-ordinated' marketeconomy according to the VoC thesis,is deemed as attractive as the UK, a'liberal' market economy. Table 3signifies the general FDI inflows forcertain years without distinguishingsectors (here, Germany even overtakesthe UK). While there is no data specifi-

cally for the biopharmaceutical sector,FDI Media Information (2005) showsthat there were 23 FDI projects in theUK and 18 in Germany for the pharma-ceutical sector as a whole.

Table 3: FDI inflows (as a % of GDP)1995 1999 2002

UK 1,8% 5,8% 1,6%D 0,5% 2,6% 1,9%

Source: PICTF 2004

Table 2: Products in pipeline in 2002:comparison of Germany and UKGermany UK

Products inpipeline

200 194

* pre-clinical 117 65

* clinical phase I 34 50

* clinical phase II 22 56

* clinical phase III 3 23

Source: Ernst & Young 2004


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Figure 8 - Number of drugs introduced by UK and German firms

0

5

10

15

20

25

30

35

40

45

Germany UK

1991-2000 1994-2003 Source: PICTF, 2004

Number of drugs introduced by nationality

Figure 9 - Relative weight of research in the pharmaceutical industries

0

2

4

6

8

10

12

14

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

Germany UK

Percentage of "world" pharmaceutical ind ustry R&D

Source:PICTF, 2004

Figure 10 - R&D efficiency

0

0,2

0,4

0,6

0,8

1

1,2

1,4

1990-1999 1991-2000 1992-2001 1993-2002

Germany UK

Percentage of Pharmaceutical Patents / Percentage of Industry R&D

Source: PICTF, 2004


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Having now presented empirical sup-port to show that the postulateddifferences between the German andBritish economies fail to be revealed

when the recent development of bio-pharmaceuticals is examined, theobserved convergence needs explana-tion.

3.3 Explaining the data: organisa-tional alignment via innovationnetworksWhy do we observe these strongsimilarities in comparing the UK's andGermany's biopharmaceutical indus-tries? The data summarised in theprevious sections clearly offer nosupport for the research hypothesesarising from the VoC and NIS literaturethat predicted large differences in the

two national settings. One possibilityis that the national innovation sys-tems, i.e. the institutional frameworks,

of both countries, have themselvesconverged. However, this potentialexplanation is ruled out by recentstudies focussing on their persistentdifferences (cf. Amable/Barr/Boyer1997; Balzat 2004). Another potentialexplanation could be that the bio-pharmaceutical sector has somespecial characteristics which mightoverwhelm the effects of nationalinstitutional differences.

Our hypothesis is that all knowledge-intensive industries have characteris-tics which differ greatly from otherindustrial sectors: these characteristicsdirectly affect innovation performance

and provoke network formation andinternationalisation. In the long run,the network effects of collaborativeinnovation mitigate or even overcomethe effects of differences in institu-tional frameworks.

What are the special characteristics ofthe biopharmaceutical sector thattrigger interactional collaborativeinnovation? Taking drug developmentas the most prominent feature of

radical innovation in the biopharma-ceutical industries, the first character-istic is the demand for up-to-dateexpertise which requires a permanentconnection with the frontiers of re-search. For example, Herrera (2001)states: "research is the engine ofEurope's Biotech Industry". Biotechfirms are permanently "operating atthe cutting edge of a set of technolo-gies" (ibid) closely connected to uni-

versities and public research organisa-

tions. Furthermore, the developmentof a single drug needs a combinationof different knowledge stocks andspecialised expertise in a number offields; it requires, for example, exten-sive clinical testing. Small firms suchas university spin-offs have to build upa close connection to hospitals and bigpharmaceutical firms in order to getaccess to relevant knowledge in theseareas.

Because biopharmaceutical innova-tions rely on 'combinatorial technolo-

Figure 11: Time spans for market introductionof noveltiesGermany

United Kingdom

0

0,5

1

1,5

2

2,5

1996-2000 1997-2001 1998-2002 1999-2003

approval in market - launch in market

application in market - approval in market

1st w orld application - application in marketGermany

Source: PICTF, 2004

0

0,5

1

1,5

2

2,5

1996-2000 1997-2001 1998-2002 1999-2003

approval in market - launch in market

application in market - approval in market

1st w orld application - application in market

United Kingdom

Source: PICTF, 2004


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gies', large firms also have a need fornetworking: "Vertical integration is nolonger the only way for pharmaceuticalcompanies to have access to comple-mentary and specific assets, especiallyat the first stage of cooperation. Theytake advantage of the complementaryand combinatorial nature of biotech-nologies to conceive new organisa-tional forms within a cooperative

relationship with both start-ups andpublic or quasi-public research organi-sations. Most pharmaceutical compa-nies are engaged in more or lesscomplex operations such as mergersand acquisitions, joint ventures, cross-licensing and, more generally multi-firm alliances. They often involve

several bilateral strategic allianceswith different actors. In this context,the strategy is to focus on many part-nerships with widely diverse compe-tencies and goals. At the industry level,this leads to a very complex mappingof ties between actors" (Staropoli 1998:13-23).

How can these high demands forexpertise, knowledge and R&D in

various disciplinary fields be satisfiedwhen they require the collaboration ofactors from all over the world locatedin different types of organisations? By

using the national public and privateR&D efforts as input indicators and thenumber of national patents and othersimilar measures as output indicators,the VoC and NIS literatures concludethat national knowledge bases arerestricted. External and in particularforeign knowledge sources are notadequately considered. Facing theglobal knowledge requirements men-

tioned above, these restrictions mustbe overcome on the firm level byactors who combine their compe-tences and expertises competencesthat cannot necessarily be found onlyat the national level. Innovation per-formance in knowledge-intensiveindustries, either incremental or radi-

cal, can only be achieved via interna-tional and inter-organisational part-nerships.

Accordingly, we observe high andincreasing collaborative activity inknowledge-intensive industries. Illus-trating the general trend, figure 12shows the new international strategictechnology alliances for IT and bio-technology. The amount of collabora-tive activity at least matches andsometimes overtakes the cumulativenumber of collaborations for all other

Figure 12: Increasing network activity in knowledge-intensive industriesNumber of New International Technological Alliances of European Firms

0

20

40

60

80

100

120

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

Biotechnology Information Technologies

Source: Science and Engineering Indicators, 2002


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technologies (National Science Board2002 Fig. 2-36).

In knowledge-intensive industriesnetwork formation does not seem to

be a passing phenomenon, whichdisappears with the maturation of theindustry. Instead, networks persist asthe main structuring principle of thebiotech industry despite firms chang-ing their components, attachmentstrategies and structural properties.For example, in the UK and Germanbiopharmaceutical industries, collabo-rative activity can be observed as apermanent feature. Collaboration is soimportant that a number of "match-

making firms (e.g. PharmalicensingIntl. Inc., BioScan) have been estab-lished whose role is to inform compa-nies about possible internationalpartners.

For example, 86 percent of Germandedicated biotechnology firms haveR&D partnerships either with otherfirms or with research organisations(EBIS 2000). Not surprisingly, for bothGermany and the UK, we observe a

strong increase of collaborative activityin the early phase of the development

of their biotech industries because ofmissing absorptive capacities and theinflexibility of established big firms(large diversified firms, LDFs), whichhave to rely on specialised small hightech enterprises (dedicated biotechfirms, DBFs) to act as translators inorder to bridge knowledge gaps(Pyka/Saviotti 2005). For their part,DBFs need the LDFs as commercialis-ers of their technological knowledge.

As a result, we observe a change of thesectoral knowledge base: LDFs collectcompetences via fusions and acquisi-tions; and DBFs and LDFs form net-

works in order to benefit from one

another's competences. The observedearly co-operations between LDFs andDBFs are not restricted to a nationallevel, as can be seen in table 4.

Later in the development of the sector,the composition, attachment strategiesand structural properties of the net-

works change to a stronger focus onDBF-DBF partnerships and to thegrowth of financing as a tie betweenfirms, in addition to R&D links (for adescription of a similar evolution ofnetwork dynamics in the US biotechindustries, see Powell et al. 2005). The

Table 4: Examples of international LDF-DBF networks

LDFAHP

Bayer

Boeh.Ingel.

Dupont

Merck

EliLilly

GlaxoWellc.

Hoechst

Roche

Merck&Co

Novartis

Pfizer

SKB

Warn.Lamb.

Zeneca

DBFAffymax 2 1 1 1 2

Affymetrix 1 2

ArQule 2 1

British Biotech. 1 2 1 1 2

Celltech 1 2 2

Chiron 1 1 1 1

CoCensys 1 1 1

Human Genome Scie. 1 3

Incyte Pharma 1 1 1 1 1 1

Millenium Bio Therap. 1 2 1

Neurogen 1 3

Onyx 1 1 2

Repligen 1 1 2 1 2

Scios 1 1 1 1 1

Sequana Therap. 1 1 1 1SIBIA 1 1 1

Xenova 2

Source: Pyka/Saviotti 2000: 28


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trend towards international networkformation also increases. Figure 13shows the co-patenting activity ofGerman and UK biotech firms withforeign partners.

UK firms have a higher proportion ofco-patents but have less patents intotal, which means that the two curvesconverge, providing yet more evidenceof the similarities of the industries inthe two countries, noted above.

Another factor leading to networkformation and internationalisation isthe biopharmaceutical industry's needfor capital. To develop a new drug,capital of about 600 Mill. EUR musttypically be available and the develop-

ment will need a period of about 10-12years until the point when commer-cialisation is a possibility. The im-mense resources required for R&D,clinical testing and marketing exceedthe capabilities of single firms. Therisks and uncertainty inherent in newdrug development are indicated by thehigh exit rate of projects and firms.

When Germany is stated in the VoCand NIS literature to be at a disadvan-

tage in the area of radical innovationssuch as drug development or in suc-

cessfully establishing knowledge-based industries as a whole, it is thecapital requirements and risks that aremainly considered. Summarising, it isargued (Casper/Kettler, 2001: 16f.) thatthe national institutional framework in

Germany makes money scarce for risk-intensive and expensive projects (seeabove). However, this is true at leastin these dimensions for any nationaleconomy, including the UK. To over-come the problem, network formationis the strategy of choice in both Ger-many and the UK. The missing re-sources are gained within globally-oriented innovation networks (interna-tional VC-DBF partnerships; interna-tional DBF-LDF partnerships, cross-

border mergers and acquisitions). Inaddition we have shown in section 3.2that foreign direct investment is im-portant for the biotechnology-basedindustries as an external source forfinancing innovation.

4 ConclusionsNational frameworks alone cannotprovide the necessary knowledge

stocks and financial resources toproduce innovation in knowledge-

Figure 13: Biotechnology patents (UK and D) with foreign partners

0

20

40

60

80

100

120

140

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003

Germany UK

Source: OECD Corporate Data Environment and own estimations


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intensive industries. Complementingthe collaborative activity on the na-tional and regional level which isalready significant, we observe in-creasing international network forma-tion as the main organisational featureof research and production. Thesecollaborations are intended to alleviatethe disadvantages stemming from therestrictions of national institutionalinfrastructures.

While heterogeneity persists at thelevel of institutional frameworks andpath-dependent innovation environ-ments, the differences are of decreas-ing relevance in knowledge-intensive

industries, where networks dominateindustrial organisation and lead toconvergence and alignment. In knowl-edge-intensive sectors such as thebiopharmaceutical industry, the neces-sities of knowledge exchange, transfer,co-operation and diffusion betweenfirms leads to a strong structural anddynamic alignment of national indus-tries. Inter-organisational networksseem to offer a kind of "second orderco-ordination alongside institutionalframeworks shaping economic action.Commonalities and differences ofdifferent "capitalisms (as proposed bythe VoC approach) or national institu-tional frameworks (the NIS approach)must be re-considered for modernknowledge societies.

Research is necessary to show hownetworks perform this alignmentprocess and which network featuresqualify for what organisational re-

flexes. Social network analysis (e.g.Granovetter/Swedberg 2001; Kadushin2004) suggests that dense networks(e.g. those now being established inthe knowledge-based industries) tendto show the alignment of members andprocesses as a typical effect due toknowledge distribution in networks.The network members become moresimilar not only in their knowledge butalso in their intentions and strategicbehaviour. Agent-based modelling ofnetwork formation in knowledge-based industries (Gilbert et al 2001,

Ahrweiler/Pyka/Gilbert 2004) shedssome light on the procedural aspectsof these issues. Nevertheless, furthertheoretical, empirical and modellingefforts are required to work on thecomplex features of innovation dy-namics and industrial organisation inknowledge-based economies.

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