POLICIES KNOWLEDGE-INTENSIVE COLLABORATIVE NETWORKS

The Center for International Science

and Technology PolicyT h e G e o r g e W a s h i n g t o n U n i v e r s i t yNicholas S. Vonortas

POLICIESPOLICIESKNOWLEDGE-INTENSIVE KNOWLEDGE-INTENSIVE

COLLABORATIVE NETWORKSCOLLABORATIVE NETWORKS

Nicholas S. VonortasCenter for International Science and Technology Policy

& Department of EconomicsThe George Washington University



PART I

INTRODUCINGBUSINESS PARTNERSHIPS:

Definitions - Rationale



INTRODUCINGSTRATEGIC BUSINESS PARTNERSHIPS

• During the past 3 decades, collaborative strategies in international business have gained popularity.

• Particularly in high technology industries, leading firms have increasingly used joint ventures, joint R&D, technology exchange agreements, direct minority investments, and sourcing relationships.




• All these inter-firm relationships are short of complete merger, but deeper than arm’s-length market exchanges.

• Such relationships involve mutual dependence and shared decision-making between two or more independent firms. When R&D is a focus of the partnership, universities and other research institutes may also participate.

• They are characterized here as strategic business partnerships (or alliances).




• Several databases tracking strategic partnerships show that the rate of formation of such partnerships has accelerated dramatically since the late 1970s.

• This dramatic increase reflects non-equity agreements by and large. In contrast, equity based partnerships have kept a fairly low profile.

• Current conditions in the global economy make these alliances advantageous, perhaps necessary, for firm competitiveness in many industries.



INTERNATIONALSTRATEGIC BUSINESS PARTNERSHIPS

Three major and inter-related factors have been driving the surge of international partnering.

– Globalization• Multinational companies have relentlessly pushed into new

geographical and product markets.

– Technological Change• The pace of technological advance has accelerated, partly as a result

of increasing competition through globalization.

– The notion of “core competency”• Increasing international competition and rapid technological advance

have robbed firms of their ability to be self-sufficient in everything they do. The idea now is, do internally what you do best and outsource the rest through partnerships



DEFINITION: JOINT VENTURES

• In the mid-1980s, OECD defined joint ventures as activities “…in which the operations of two or more firms are partially, but not totally, functionally integrated in order to carry out activities in one or more of the following areas:

• buying or selling operations;

• natural resource exploration, development and/or production operations;

• research and development operations;

• engineering and construction operations”



DEFINITION: JOINT VENTURES

• In general, the motives for setting up a joint venture were understood to include:

• using complementary technology or research techniques;

• raising capital;

• spreading the risks associated with establishing an enterprise in a new product or geographical area;

• achieving economies of scale;

• overcoming entry barriers to domestic and international markets; and,

• acquiring market power.”



HISTORY OF JOINT VENTURES

• Up until the late 1970s, inter-firm cooperation was dominated by equity partnerships

• There were few exceptions, involving research consortia organized under government auspices in industrialized countries such as the Engineering Research Associations in Japan and several research consortia organized in the United States in the 1970s to tackle energy problems




• Two important changes have taken place since the early 1980s in terms of inter-firm cooperation:

– First, the extent of cooperation has increased very much resulting in big numbers of national and international partnerships

– Second, the organizational structure of cooperation has changed dramatically, reflecting the increasing importance of organizational flexibility. Non-equity partnerships are currently dominating the landscape




• Consequently, the joint venture definition shown previously (requiring the establishment of a new entity separate from the parents) proved too rigid to be able to accommodate the rapidly growing variety of institutional mechanisms to transfer organizational and technological knowledge

• The need for a better definition was met with a broader concept: the concept of a strategic partnership (alliance)



DEFINITION:STRATEGIC BUSINESS PARTNERSHIPS

• A strategic alliance (partnership) was defined by David Teece as a web of agreements whereby two or more partners share the commitment to reach a common goal by pooling their resources together and coordinating their activities.

• A strategic partnership denotes some degree of strategic and operational coordination and may include things such as joint research and development (R&D), technology exchanges, exclusionary market and manufacturing rights, and co-marketing agreements. Partnerships may, or may not, involve equity investments.



PRIVATE SECTORINCENTIVES TO PARTNER

• Access product and financial markets;

• Share costs of large investments such as as R&D;

• Share risk, reduce uncertainty;

• Access complementary resources and skills of partners, such as finance, complementary technologies;

• Benefit from research synergies;

• Accelerate return on investments through more rapid diffusion of assets;




• Deploy resources efficiently to create economies of scale, specialisation and/or rationalisation;

• Increase strategic flexibility through the creation and optimal exploitation of new investment options;

• Unbundle the firm’s portfolio of intangible assets, and selectively transfer components of this portfolio;

• Co-opt competition;

• Attain legal and political advantages in host countries.




• More broadly, partnerships have such virtues as flexibility, speed, informality, and economy.

• They can be put together in little time and be folded up just as quickly.

• They can involve little paperwork. In comparison to market internalisation through mergers and acquisitions, a close analogy of partnerships would be “love affairs instead of marriages”.





STRATEGIC TRADE-OFF OF COLLABORATION

Regardless of the strategic goal, collaboration with another firm always implies a trade-off between:

• greater access - to markets, finance, other resources, capabilities; and

• lesser control - of strategic decision making, day to day management, technological and other kinds of knowledge.



PART II

POLICY FORRESEARCH PARTNERSHIPS



Intervention Rationale

• The basic justification for government action was market failure.

• In R&D partnerships, the arguments initially revolved around the inability and unwillingness of the private sector to undertake research that is risky and imperfectly appropriable.

• Hence the call for supporting collaborative pre-competitive research.

This of course agreed with the political constraints of the Commission.



Intervention Rationale

• Later the justification expanded to arguments for systemic failure.

• Some issues were said to be bigger than any individual organization - or small groups of organizations - to tackle. An example is the transition into new generations of technology.

• Such arguments have underlined the ideas of European Technology Platforms and their programmatic implementation into Joint Technology Initiatives in FP7.



Policy for RPs• S&T is one area with relatively little to show in terms of

harmonization and cohesion between the policies of EU member states.

• The NIS of EU member states remain rather dissimilar due to historical, cultural, and other factors related to the development stage and consequent needs and capabilities.

• The STEP-TO-RJVs project demonstrated the same phenomenon in one specific area of S&T policy – cooperation in R&D. Such diversity is increasingly viewed as a strength of the European system.



Policy for RPs• Still, the ERA concept presupposes a certain degree of

cohesiveness and basic goal harmonization across member states.

• One way the Commission has tried to narrow the gaps (e.g., national R&D funding) and address the discrepancies (e.g., areas of focus and specific policy tools) has been the establishment of the Framework programme.

• Among others, the 6th FWP and the current 7th FWP envisioned a genuine partnership between the EU and its member states and with other European scientific cooperation organizations.



Policy for RPs

• The project “S&T Policies Towards RJVs” was launched in the late 1990s with teams representing France, Greece, Ireland, Italy, Spain, Sweden and the United Kingdom. That is an amalgam of three kinds of member states, including large R&D-spending states, developed smaller states, and cohesion states.

• As a necessary first step was to summarize the S&T policies related to RJVs of these countries plus Japan and the US. In addition, partners also reviewed competition policies and IPR policies that affect RJVs.



Policy for RPs• The support of international consortia has been the main funding

mechanism of FWPs since inception.

• Awareness and support of cooperative R&D has also increased at the national level:

Cohesion states without an extensive tradition of sophisticated industrial and S&T policies have made significant steps in that direction.

Most of the rest seem genuinely trying to do more than before.

The UK sometimes appeared to consider FWP programmes as substitutes of its own, but continued to promote collaboration and networks in various, largely non-monetary ways.



Policies for RPsExtensive differences between member states were reported:• Policy approaches have ranged from complete indifference to

the issue until recently (Ireland), to lukewarm policies (Greece, Italy), to decreasing attention (UK), to established network systems (Sweden), to highly determined programmes to support collaborative R&D (France, Spain).

• The level and type of support have varied widely as have the specific policies and programmes, their technological focus, and the numbers and kinds of participating economic agents.

Amidst this variation, the European Commission’s policies have played a boosting and cohesive role.



Policies for RPs

The policies of Japan and of the US have also been quite different from those in Europe reflecting, at least in part, the general S&T outlook in these countries:

• In Japan, the emphasis on cooperative R&D continues. Government sponsored RJVs, however, seem to have made the transition since the 1980s from primarily mechanisms assisting whole sectors to catch up with world practice to mechanisms creating a richer and more effective technological superstructure for a high group of high technology sectors.



Policies for RPs

• In retrospect, the US can be argued to have followed a rational approach to accommodating rising levels of R&D cooperation. It first changed its institutional structure and relevant legal system. It then moved forward to put in place specific programmes to actively promote cooperative R&D.

• The EU approach appears to have been the reverse of the US approach, but no less rational in the face of the specific situation of the region.



Several landmark policy initiatives between the early 1980s and the mid-1990s paved the way to a new policy approach to innovation and the emerging economy:

Domestic Policy Review of Industrial Innovation – 1978 Stevenson-Wydler Technology Innovation Act – 1980 Bayh-Dole University and Small Business Patent Act – 1980

Research and Experimentation (R&E) Tax Credits – 1981 Small Business Innovation Development Act – 1982 Merger Guidelines – 1982 Eleventh Circuit Court of Appeals for IP – 1982 President’s Commission on Industrial Competitiveness – 1983 Engineering Research Centers; Industry-University Cooperative Research Centers – 1983 National Cooperative Research Act – 1984 Federal Technology Transfer Act – 1986 Omnibus Trade and Competitiveness Act – 1988 National Cooperative Research and Production Act – 1993

CENTER FOR INTERNATIONAL SCIENCE AND TECHNOLOGY POLICY

T h e G e o r g e W a s h i n g t o n U n i v e r s i t y



Policy for RPs

• Confronted with a large collection of significantly variable national S&T policies, the Commission first moved to put in place its own supra-national programmes for cooperative R&D before trying to harmonize policies across member states.

• Harmonization and cohesion continue but the process has been a slow one.

• Almost 30 years later, the 6th and 7th FWP and ERA try to bridge the national S&T programmes and form a coherent whole.



Basic Lessons• EU policies have become a force well reckoned by member

state governments. EU policies have very much influenced policies at the national level and, in certain cases, shaped them to the extent of straightforward translation (cohesion countries).

• Policy-decision makers across countries have placed important value on cooperative R&D but there is extensive variability in policy approaches.

• The ERA is supposed to be the cohesive force that recognizes and accepts variability.



PART III

PARTNERSHIPS & NETWORKING IN S&T FOR DEVELOPMENT



Partnerships for Development

The proliferation of partnerships during the past couple of decades has raised expectations of accelerated growth through faster access to markets and technologies and greater learning possibilities.

There is evidence that inter-firm partnerships can be an extremely useful tool to assist developing country firms (and poorer regions) in their efforts to catch up.

Partnerships can accordingly assist countries speed up the process of establishing competitive indigenous industries. Partnerships can also play a major role in mobilizing the necessary resources and technological expertise to upgrade lagging infrastructure.



Partnerships for DevelopmentThe evidence is, however, still concentrated in certain

geographical areas and sectors. This has been interpreted to imply that the expectations of widespread catch-up opportunities through partnerships have not yet materialized.

However, intensive international inter-firm collaboration is a relatively new phenomenon where, with few exceptions, developing countries have made their presence felt only very recently. In other words, it is simply too early to tell.




It is also possible that analysts have tried to extrapolate too much too fast from the experience of developed countries, in the process missing important flags.

The available empirical information has overwhelmingly been on formal partnerships. In contrast, we have a lot of anecdotal but little systematic information on informal partnerships.

Available anecdotal evidence strongly indicates that informal partnering probably accounts for apparently the largest share of partnering activity in industry. It involves firms and all other kinds of organizations, but it involves especially SMEs in proximate geographical areas.




We have developed various terms to capture aspects of more informal modes of interaction. We talk about clusters. We talk about districts. We also talk about networks.

Each term means something different, but they also share considerable ground: the willingness and ability to interact closely with the surrounding environment, with peers, with buyers and suppliers – by and large on an informal basis. An expanding literature has, in the past few years, tried to amass evidence of such interaction and of policies that promote it in developed and developing countries




Formal and informal partnering should be seen as a continuum.

Then, the question is not anymore whether partnering helps developing country/region firms to grow competitive. The question rather becomes which kind of partnering may be more appropriate – or more prevalent – at different stages of development and in different sectors.




Formal partnerships require strategy formulation and partner contribution, whether in financial resources, intangible assets, market familiarity, market access, etc. Frequently, the required level of strategy sophistication and resource commitment is considerable.

It is, thus, quite possible that these requirements raise the bar too high for the mass of (mainly small and unsophisticated) firms in the majority of developing countries. Hence, it could be argued, the relatively slow trickling down of partnering to the majority of developing countries.




Still, this leaves many other interactions for these agents to pursue. It seems quite probable that informal partnering through networks and clusters is a way for many relatively disadvantaged developing country firms to become stronger, more competitive, and to meet the minimum capability prerequisites in order to graduate to formal partnerships.

Governments may be wise to try addressing most developing country SME problems related to size and competitive position through networks (often more vertical, supplier-buyer relationships) and clusters (regional, more horizontal, agglomerations).



PART IV

COLLABORATE TO COLLUDE? Multimarket and Multiproject Contact

in R&D



Collaborate

Competitiveness Challenge & Market Failures National Cooperative Research Act (1984) Research Joint Venture (RJV) “Organizations or contractual agreements involving at least two entities with the primary purpose to engage in R&D.”

Policy for Industrial R&D Cooperation since 1980s

Restore private incentives Acquire complementary resources Exploit economies of scope Create new investment ‘options’

Restrict parallel approaches Moral Hazard Lessen competition Decrease social surplus

Alleged Advantages Potential Drawbacks



Collaborate

New RJV Announcements between 1985 - 1999

Total = 796



Collude

Multi-Market Contact Arguments

Research Joint Ventures (RJVs)

Multi-Project Contacts (MPC)

Multi-Market Contacts (MMC)

Collusion LowerConsumer Surplus

Anti-Competitive Behavior



Question

Is Multi-Project Contact through RJVsa Cause of Concern?

Safeguards against anti-competitive behaviorMPC & MMC

Multi-Project Contact

Multi-Market Contact

Foreign Participation Technological & Market Uncertainty “Porous Constellation”

YES NO



Data

Registered with DOJ & FTC under NCRA (1984) & NCRPA (1993)

PROJECT Table

* ProjectID* Project Name* Project Initiation Date* Project Purposes* Technical Area* Industrial Area

MEMBERSHIP Table

* ProjectID* EntityID* Membership Name* Participating Date* Membership Status

ENTITY Table

* EntityID* Entity Name* Type* Country* Primary Industry

Various Data Sources at Entity Level * Organizational Type * Origin of Country * Business Lines (SIC) * Number of Employees * Etc.

NCRA RJVs (1985 – 1999)

Database Structure



Cooperative Activities of All Identified Entities

Data

No. of Memberships Memberships Entities % (Entities)

1 2,801 2,801 65.75

2 1,382 691 16.22

3 798 266 6.24

4 504 126 2.96

5 410 82 1.92

6 to 10 1,099 142 3.33

11 to 20 1,270 89 2.09

21 to 50 1,260 40 0.94

more than 50 1,933 23 0.54

Total Identified Memberships 11,457

Total Memberships 14,019

Total Identified Entities 4,260 100

7%50%

2/3



Multi-Project Contacts in NCRA RJVs: AT&T

Honeywell(3728)

Kodak(3861)

IBM(7370)

SAIC(8700)

DEC(3570)

HP(3570)

Motorola(3663)

Fujitsu(7373)

Nortel(3661)

TI(3674)

Novell(7372)

Lucent(3661)

Sun(3571)

Hitachi(3570)

Verizon(4813)

GM(3711)

Tandem(3571)

Siemens(3600)

Apple(3571)

Boeing(3721)

BT(4813)

Intel(3674)

NEC(3661)

NTT(4813)

Groupe Bull(6719)

Alcatel(3661)

Ericsson(3663)

OKI(6719)

Philips(6719)

Rockwell(3620)

Unisys(7373)

DuPont(2820)

Harris(3663)

Lockheed Martin(3760)

MCI WorldCom(4813)

Toshiba(3570)

Xerox(3577)

GE(3600)

Mitsubishi(6719)

Nokia(3663)

Tohomson-CSF(3812)

SBC(4813)

Southwestern(4813)

Sprint(4813)

Racal(6719)

CDS(7372)

Microsoft(7372)

NSC(3674)

Oracle(7372)

AT&T(4813)

13

41 33 29 2628

25

22

22

21

21

23

21

18

18

17

20

21

17 17

17

15 16 1714141414 1413

13

13

13

13

12

12

12

12

32

11

11

13

12

11

11 11 11 11 11



MPC & MMC in NCRA RJVs

DuPont 2820 Texaco 2911 33 1AT&T 4813 HP 3570 32 1GM 3711 IBM 7370 32 3BP Amoco 2911 USX-Marathon 2911 30 2Shell 1311 Texaco 2911 30 5AT&T 4813 SAIC 8700 29 0Chevron 2911 Phillips 2911 29 4IBM 7370 Motorola 3663 29 2AT&T 4813 Nortel 3661 28 1BP Amoco 2911 UNOCAL 1311 28 4Exxon Mobil 2911 UNOCAL 1311 28 6IBM 7370 Nortel 3661 28 1Phillips 2911 Texaco 2911 28 5AR 2911 DuPont 2820 27 1Fujitsu 7373 IBM 7370 27 6Texaco 2911 UNOCAL 1311 27 6AT&T 4813 Motorola 3663 26 1Chevron 2911 UNOCAL 1311 26 4Fujitsu 7373 HP 3570 26 4AT&T 4813 Fujitsu 7373 25 2Chevron 2911 USX-Marathon 2911 25 2DEC 3570 GM 3711 25 0DuPont 2820 Shell 1311 25 3Exxon Mobil 2911 USX-Marathon 2911 25 2GM 3711 HP 3570 25 1GM 3711 TI 3674 25 1IBM 7370 TI 3674 25 4

Total 1,999 160

DuPont 2820 Texaco 2911 33 1AT&T 4813 HP 3570 32 1GM 3711 IBM 7370 32 3BP Amoco 2911 USX-Marathon 2911 30 2Shell 1311 Texaco 2911 30 5AT&T 4813 SAIC 8700 29 0Chevron 2911 Phillips 2911 29 4IBM 7370 Motorola 3663 29 2AT&T 4813 Nortel 3661 28 1BP Amoco 2911 UNOCAL 1311 28 4Exxon Mobil 2911 UNOCAL 1311 28 6IBM 7370 Nortel 3661 28 1Phillips 2911 Texaco 2911 28 5AR 2911 DuPont 2820 27 1Fujitsu 7373 IBM 7370 27 6Texaco 2911 UNOCAL

DuPont 2820 Texaco 2911 33 1AT&T 4813 HP 3570 32 1GM 3711 IBM 7370 32 3BP Amoco 2911 USX-Marathon 2911 30 2Shell 1311 Texaco 2911 30 5AT&T 4813 SAIC 8700 29 0Chevron 2911 Phillips 2911 29 4IBM 7370 Motorola 3663 29 2AT&T 4813 Nortel 3661 28 1BP Amoco 2911 UNOCAL 1311 28 4Exxon Mobil 2911 UNOCAL 1311 28 6IBM 7370 Nortel 3661 28 1Phillips 2911 Texaco 2911 28 5AR 2911 DuPont 2820 27 1Fujitsu 7373 IBM 7370 27 6Texaco 2911 UNOCAL 1311 27 6AT&T 4813 Motorola 3663 26 1Chevron 2911 UNOCAL 1311 26 4Fujitsu 7373 HP 3570 26 4AT&T 4813 Fujitsu 7373 25 2Chevron 2911 USX-Marathon 2911 25 2DEC 3570 GM 3711 25 0DuPont 2820 Shell 1311 25 3Exxon Mobil 2911 USX-Marathon 2911 25 2GM 3711 HP 3570 25 1GM 3711 TI 3674 25 1IBM 7370 TI 3674 25 4

Total 1,999 160



Foreign Participation

Identified Entities by Country



Technological & Market Uncertainty

Primary Technical Areas of RJVs



“Porous Constellation”

RJV Membership Changes



Collaborate to Collude?

Multi-Project Contact

Multi-Market Contact

Foreign Participation Technological & Market Uncertainty “Porous Constellation”

Mixed Evidence

Alert to enhanced possibility of market concentration Focus on intersection of MMC & MPC Counterbalance between - Advantages of Collaboration in Industrial R&D and - Danger of Anti-Competitive Behavior

Policy Implications



PART V

USING SOCIAL NETWORKSTO EVALUATE

R&D PROGRAMS



PRIOR RESULTS ON IST-RTD PRIOR RESULTS ON IST-RTD NETWORKSNETWORKS



Prior Results European IST RTD Networks

The network of research collaborations has:

• A self-organizing structure, dominated by “hubs”, which are also key nodes in National research networks

• A scale-free architecture at the thematic levels



Prior ResultsEuropean IST RTD Networks

European research is characterized by “small world” connectivity

Strong tendency of scientists to cluster around national communities

Strong tendency to cluster with research disciplines and within industrial sectors

The funding structure has a strong influence on research co-operations




As a result of the new Integrated Projects and Networks of Excellence:

• The density of links is higher

• The share of participants in the principal component is higher

• The average path length is lower

• Large firms and research institutes are more dominant as gate-keepers of collaboration

• Small companies are “crowded out” relative to FP5




The IST RTD network as a whole has “small world” characteristics - but this is not true for each and every one of its programmes

FP6 more likely than other research collaboration frameworks to:

• Connect universities and industry• Connect different research themes• Include new Member States• Include key patent-holders• Include SMEs



THIS STUDY ON IST-RTD THIS STUDY ON IST-RTD NETWORKSNETWORKS



Towards an ERA for IST:Overall Objectives

Develop and apply a quantitative analytical framework for the assessment of the characteristics and performance of networks supported by IST RTD in FP5 and FP6.

Analyze knowledge and partnership networks in selected IST RTD domains, concentrating on network nature, topology, time evolution and effectiveness.

Supplement quantitative information with some qualitative information, and inter-organizational networks with inter-personal networks



Towards an ERA for IST:Evaluation Questions

• How do the characteristics of the IST-RTD partnership and knowledge networks compare with the characteristics of the global partnership and knowledge networks of IST-RTD companies and with the characteristics of the related global networks?

• How well are the companies participating in IST RTD programs positioned in the global partnership and knowledge networks?




• How effective are IST-RTD networks as mechanisms for transmitting knowledge?

• Are the Integrated Projects (IPs) and the Networks of Excellence (NoEs) creating leading “knowledge hubs”?

• What makes these “knowledge hubs” effective?




• To what extent does the prominent network status of certain IST RTD companies of clusters match the EU technological leadership in certain areas?

• Are the global networks of selected “hub” companies with extensive ICT supply chains represented in the FP6 IST RTD?

• Are the perceived national IST “knowledge hubs” well integrated into the FP6 network?



Selection of IST

technology domains

IST-RTDFramework Programme 6

Matching of IPC codes with technological domains

Patent examiners

Field experts

Matching of SIC codes with technological domains

INNET alliances

EP-CESPRI patents/citations

KNOWLEDGE NETWORKS (Ib, IIb, IIIb)

PARTNERSHIP NETWORKS

(IIa, IIIa)

PARTNERSHIP NETWORK Ia



Towards an ERA for IST:Network Types

• IST-RTD partnership network

• IST-RTD knowledge network

• Global partnership network of IST-RTD project participants

• Global knowledge network of IST-RTD project participants

• Global partnership network akin to the E technology units

• Global knowledge network akin to the E technology units



Towards an ERA for IST:Examined Programs

FP 5

FP6

Key Actions Thematic Areas

1. System and services for the citizen

2. New method of wok and electronic commerce

1. Applied IST research addressing major societal and economic challenges

2. Communication, computing

and software technologies

4. Essential technologies and infrastructures

3. Components and micro -systems



TA 1-2-3 FP6

Not SelectedNot Selected 115115 27,327,3

SelectedSelected 307307 72,772,7

Projects

Not selected27%

Selected73%



TA 1-2-3 FP6TA 1-2-3 FP6

Participants

Not selectedNot selected 13401340 21,821,8

SelectedSelected 48144814 78,278,2

Not selected22%

Selected78%

ParticipantsParticipants: counted once for every project they have participated in



By instrument(projects)

CA: Coordination ActionIP: Integrated ProjectNoE: Network of Excellence

SSA: Specific Support ProjectSTREP: Specific Targeted Research Project

TA 1-2-3 FP6TA 1-2-3 FP6

CA IP NoE SSA STREP

0

0,1

0,2

0,3

0,4

0,5

Not Selected

Selected



Organization Type

HE: Higher EducationIND: industry

REC: ResearchOTH: Other

TA 1-2-3 FP6TA 1-2-3 FP6

HE INDOTH

REC

0

0,05

0,1

0,15

0,2

0,25

0,3

0,35

Not Selected

Selected



Not SelectedNot Selected Large CompanyLarge Company 10321032 21.1521.15

SMESME 260260 21.1721.17

SelectedSelected Large CompanyLarge Company 38463846 78.8578.85

SMESME 968968 78.8378.83

SMEs and Large Enterprises

TA 1-2-3 FP6TA 1-2-3 FP6

SMELarge

Company

00,1

0,20,3

0,4

0,5

0,6

0,7

0,8

Not Selected

Selected



Indicative Analysis: 3 subjects



Subject 1: Identifying HUBs and their relative roles



Hub definitionHub definition

• An organization is a hub in a specific network if it has many links and/or if it connects the otherwise unconnected parts of the network

The above translates into high degree centrality and/or high betweeness centrality



STYLIZED 3A PARTNERSHIP NETWORK

The node labelled “HUB 3a” is the designated Hub for this network.

This is a stylized model of Network

3a (Alliances)

Give intuition behind the concept

of a Partnership Hub

A Hub is defined as a node exhibiting high value of betweenness

and degree



STYLIZED 3A PARTNERSHIP STYLIZED 3A PARTNERSHIP NETWORKNETWORK

Yellow nodes indicate

organizations participanting in

Framework Programme.



STYLIZED 1A PARTNERSHIP NETWORK

The yellow node represents the relevant Hub in the stylized 1a partnership network

The blue node is the 3a network relevant Hub

This is a stylized model of Network

1a (FP Participants)



Links Between 1a Hubs and 3a HubsBlue nodes are the 3a network Hubs

Yellow nodes represent the

1a network Hubs

1a Hubs are strongly inter-connected and

they are also connected with 3a Hubs

3a Hubs are NOT hubs in network 1a, BUT are gateways that connect FP organizations to the global network



1A FP6 (TA1) PARTNERSHIP NETWORK

Blue nodes are the 3a network Hubs

Yellow nodes represent 1a

network Hubs

Red nodes are other 3a network

participants within distance 1 from 3a

Hubs



1A FP6 (TA1) PARTNERSHIP NETWORK (no IP)

This is the TA1 Network without the

links related to IP

The network is substantially different,

with many isolated nodes and diminished

complexity



Subject 2: Effectiveness of KNOWLEDGE HUBs



Effectiveness of Knowledge Hubs

Hubs as knowledge depositories

Hubs at the cross-road of information and ideas

• Number of Patents • Number of Citations Received• Number of Highly Cited Patents

• Degree Centrality • Betweeness Centrality



Effectiveness of Knowledge Hubs: Hypothetical Example

patent citation/patent

betweenness IIIb

degree IIIb

highly cited patent

0

0,02

0,04

0,06

0,08

0,1

0,12

KH IIIa

KH Ia

OTHER Ia



Effectiveness of Knowledge Hubs:Hypothetical Example

• closely matches that of global KHs in terms of three variables closely matches that of global KHs in terms of three variables (number of patents, network centralities);(number of patents, network centralities);

• lags seriously behind in terms of the remaining two variables lags seriously behind in terms of the remaining two variables that approximate the quality and the importance of their patent that approximate the quality and the importance of their patent portfolios;portfolios;

the FP KHs seem to perform better in diffusing knowledge the FP KHs seem to perform better in diffusing knowledge through their centrality roles in the networks than in creating through their centrality roles in the networks than in creating powerful and influential portfolios of new ideas.powerful and influential portfolios of new ideas.



Subject 3: Leadership



Leadership

Two different definitions of Leadership:

• Technology Leadership:Technology Leadership: the role played by each the role played by each organisation in the innovative process organisation in the innovative process

• Market leadership:Market leadership: the share of revenues in ICT the share of revenues in ICT among EU25 among EU25



Technology Leadership

Technology leadership is defined in terms of two Technology leadership is defined in terms of two concepts:concepts:

• Niche overlapNiche overlap concerns the crowdedness of the concerns the crowdedness of the technological area explored by organisations. Its technological area explored by organisations. Its measure is based on similarity of technological measure is based on similarity of technological antecedents (i.e. co-citation).antecedents (i.e. co-citation).

• PrestigePrestige deriving from the direct technological ties deriving from the direct technological ties between actors (i.e. direct patent citations)between actors (i.e. direct patent citations)




Four different kinds of actors:Four different kinds of actors:

• Technology Leaders:Technology Leaders: a key source of knowledge a key source of knowledge spillovers for many other organizations in the industry. spillovers for many other organizations in the industry. Their research activity is focused on the exploitation of Their research activity is focused on the exploitation of opportunities in relatively mature and therefore highly opportunities in relatively mature and therefore highly crowded fieldscrowded fields

• Technology Brokers:Technology Brokers: sources of knowledge in sources of knowledge in relatively new and relatively new and unexploredunexplored fields fields




• Technology Followers:Technology Followers: they they do not contribute do not contribute significant spillovers to other organizations and engage significant spillovers to other organizations and engage into relatively mature and crowded technological into relatively mature and crowded technological subfieldssubfields

• Isolate Organisations:Isolate Organisations: they they do not receive direct do not receive direct citations from many other organizations and are citations from many other organizations and are exploring relatively untapped technological subfields.exploring relatively untapped technological subfields.



Technology Leadership:Hypothetical Example

-0.1

-0.08

-0.06

-0.04

-0.02

0

0.02

0.04

0.06

0.08

0.1

0 1 2 3 4 5 6 7 8 9 10

Crowding

Prestige

EU-Non FP

EU-FP KH

EU-FP Non KH

Global KH

Average prestige

Average alfa

Technology leaders

Technology isolates



Technology Leadership:Hypothetical Example

This analysis might suggest:

• The number of identified leaders and brokers that participate in the Framework Programme

• The number (and identity) of those who not only participate but they can also be characterized as Partnership HUBs in the Framework Programme.



PART VI

NETWORKS OF INNOVATION IN INFORMATION SOCIETY:

DEVEKOPMENT AND DEPLOYMENT IN EUROPE



ObjectivesThe core objectives of the evaluation study were:

• To assess the effectiveness of network collaboration

and knowledge transfers between RTD, innovation

and deployment activities related to IST;

• To suggest ways of strengthening the links between

IST-RTD, innovation and deployment at the EU

and regional levels



Evaluation Questions (1)

1. Do IST-RTD networks play an important role in creating new, innovative ICT products/processes and how?

2. What are the network characteristics of the organizations that are effective innovators?

3. Do IST-RTD networks influence ICT deployment? Do they speed up the diffusion process? Do they affect the geographical distribution of deployment? Do they have a structuring effect on ICT take-up in specific geographical areas?

4. Do IST deployment networks (eTen, eContent) play an important role in deploying new, innovative ICT products/processes and how?

5. How do IST-RTD and IST deployment networks complement each other? Where are the strong and the weak links? Is there a significant overlap between the two kinds of networks? Are there common nodes, common hubs?



Evaluation Questions (2)

6. Are there opportunities for greater linkages between IST-

RTD and IST deployment networks and how could they increase the impact of current and future innovation and deployment activities?

7. What are the best institutional contexts to promote ICT take-up through innovation networks?

8. Do national/regional IST networks supported by EU structural funds play an important role in introducing and in deploying new, innovative ICT products/processes and how?

9. How do the above networks (supported by structural funds) compare with networks supported only with national/regional funds in terms of both innovation and deployment?

…these questions cannot be answered through network analysis alone, they can be answered by understanding the value of the network to the participants



Analytical StepsThe methodology involved the following steps:

• Select a thematic area of IST research and deployment: “Applied IST

research addressing major societal and economic challenges”;

• Investigate innovation and deployment activities at the EU level in the

selected thematic area and define network topology at the European level

through network and data analysis;

• Select regions and undertake quantitative and qualitative analysis of

deployment in selected regions;

• Conduct interviews with key organizations;

• Analyse patterns and relationships of networks;

• Derive lessons learned and policy recommendations.



Data Analysis for Selected Regions

Quantitative analysis: data on the characteristics of research

and deployment projects (EU, national, regional). Main

analytical objectives:

1. Analyze IST networks in terms of position and role of regional

organizations

2. Analyze RTD networks and innovation

3. Analyze RTD networks and deployment

Qualitative analysis: 66 interviews with actors in

deployment networks at the regional level.



Data and Networks Construction

IST RESEARCH Project

IST DEPLOYMENT Project

Description

European network formed by organizations participating in FP6 IST

projects

European network formed by organizations participa ting in eTen and

eContent projects

Data source Internal EC Database (not publicly available)

Internal EC Database (not publicly available)

Participants 4198 2008

Projects 249 287 Participants per

project 17 7

Organisations 2417 1634 Projects per organisation 1.7 1.2



Question 2: What are the Network Characteristics?

Network Structure

Both networks are highly connected and display Small World properties: low average distance and

high clustering coefficient as compared to a random network.

IST RESEARCH

Network IST DEPLOYMENT

Network number of nodes (organisations)

2417 1634

number of edges (links) 61686 7422 network density 0.020 0.006

size largest component 2373 (98 .18%) 1153 (70 .56%) average degree 51.04 9.08

average distance 2.5 5.08 max distance 5 11

clustering coefficient 0.0377 0.1292



Question 2: What are the Network Characteristics?Network hubs

As compared to the Research network, in the Deployment network:

• Other organizations (e.g. City Council) play a role• Private companies have a more important role

0

10

20

30

40

50

60

HE REC IND OTH

Research Network HUB Deployment Network HUB



Question 2: What are the Network Characteristics?

Gatekeepers: Bridging Research and Deployment Networks

ResearchNetwork

DeploymentNetwork

Bridging Links

Organisations Participatingin Both Networks

working as Gatekeepers

• There are 277 gatekeeper organizations

• 1/3 of the links in each of the two networks are bridging links



Gatekeepers by organisational type

HE32%

IND23%

REC31%

OTH14%

SMEs seem to play a relevant role: 45 gatekeepers are SMEs (16.7% of the total).



Lessons Learned• IST RTD networks have an integrating effect across sectors

• Networks create opportunity for knowledge sharing about new product, processes, and markets

• The research networks are denser and more interconnected than the deployment networks

• Key institutions-Gatekeepers-integrate these two networks

• Knowledge flows bilaterally within the network, but the information shared by different nodes reflects their institutional role

• The EU requirement for geographic integration bring smaller institutions together with large multinationals in ways that would not happen otherwise



Policy Recommendations• Continue efforts to strengthen ERA. Research networks could

involve more organizations that are critical local players in deployment. The latter are often different than the research intensive organizations.

• Supplement the concept of ERA with a concept that extends to deployment, and to the linkages between research and deployment, following the higher emphasis on innovation and demand side effects in Europe today.

• Develop a local/regional deployment strategy as part of IST-RTD projects, when program objectives include dissemination and application, since the deployment efforts, capabilities and skills are to a significant extent different than those relating to research.



Policy Recommendations (2)• Understand better the organizations that link knowledge “hubs”

with local economies. FP knowledge “hubs” are often international universities and research institutes, traditionally weak in local economies of Europe. Programs will depend on other, often smaller players from the local private sector to deploy. The linkages between the two types of players are of critical importance.

• Create an on-line information center/directory of regional

deployment assistance to help improve access to information.

• Streamline the application process to regional/national/European

activities for small business and research institutes.

• Create virtual technology transfer centers that focus on creating

feedback loops at the local level.

Documents

POLICIES KNOWLEDGE-INTENSIVE COLLABORATIVE NETWORKS