national innovation system and mapping innovative · pdf filenational innovation system and...

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Center for European Economic Research, ZEW

National Innovation System andMapping Innovative Clusters at theFirm Level

Part One: Institutional Mapping

by

Alfred Spielkamp and Katrin Vopel

(Please do not quote)

Mannheim, 17/10/97

For further information, please contact:Dr. Alfred Spielkamp

P.O. Box 10 34 43D-68034 Mannheim

Tel.: +49 (621) 1235-174Fax: +49 (621) 1235-170

E-mail: [email protected]

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List of Contents

1 ORIENTATION AND OBJECTIVES 3

2 THE INSTITUTIONAL MAPPING OF THE GERMAN INNOVATION SYSTEM 7

2.1 Main structure of the German System and its transfer channels 7

2.2 The business sector: Innovation and R&D activities 9

2.3 The German institutional profile 12

2.3.1 Introduction 12

2.3.2 Promotion organizations mainly project support 13

2.3.3 Supporting organizations mainly on institutional support. 15

2.3.4 Federal institutions performing R&D 16

2.3.5 University related special programs 17

2.3.6 Universities 17

2.4 Firms using the German national innovation system 21

2.4.1 Introduction 21

2.4.2 Technology transfer mechanisms and sources of information 21

2.4.3 Firms cooperation behavior 23

2.4.4 Firm’s involvement in R&D-promotion programs 27

2.5 Implications 29

3 ATTACHMENTS 32

3.1 ZEW’s data sources utilized 32

3.2 Probability model of cooperation 33

4 REFERENCES 37

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1 Orientation and objectives

There is a consensus in modern growth theory and in industrial economics about the impor-tance of innovations and the innovation system in an economy. On the ground of Schumpetera wide range of economic and policy research has tried to find clear correlations among fac-tors of capital investment and R&D investment, the performance of this investment, and theimpact of industry and institutional structure (see e.g. Schmalensee, 1989).

In the last years more attention was paid on both the complex relationship between institu-tional and economic structures and the spillovers among different markets and industries.Several empirical approaches try to find some systematic patterns of innovation performanceand growth determined by technological, institutional, and national economic conditions(Schmalensee, 1989; Mohnen, 1994; Feldman and Audretsch, 1995).

Fig. 1-1: Elements of a National Innovation System

Productivity and Growth

New Products and Processes

Industrial R&D Technology transfer

Internationalization

Financial Interrelations

NTBFs

Policy

R&D-AgglomerationIndustry structure

Human capital

Demand and Competition

Public R&D

Size of Firms

Source: ZEW’s own graphics

It has become clear in the community of innovation sciences, that national systems of innova-tion have a high impact on productivity and growth, and that economies need a variety of in-stitutions before markets can function.1 The differences in national innovation patterns are

1 At this point there are some detailed studies on the special innovation systems or innovation patterns of

European countries. OECD (1996 and 1997), see also Freeman (1974), (1988), (1990), Lundvall (1988),

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caused mainly by different sources and institutions of knowledge generating and diffusion(David and Foray, 1995).

When the system is analyzed, the emphasis is on the interdependencies between the corporateproduction apparatus and a country’s social and economic institutions, as well as furtherboundary conditions applying. In the private sector we examine the organizational structuresin terms of production and innovation activities, plus the technological relationships betweendifferent companies, and between companies and public-sector institutions. (see Fig 1-1) Inthe public sector, the focus is on boundary conditions like cultural and social factors, the edu-cational, fiscal and legal systems (e.g. regarding the protection of intellectual property), andpolicy measures affecting technology, business and the labour market.

Recent research into innovation has discovered that the actual innovation process can in mostcases no longer be depicted as a linear model of consecutive phases of innovation, where theresearch phase, product development and product design are implemented independently ofeach other in temporal succession. In the majority of industries or technologies, the phases andsub-processes involved are recursively interwoven with each other, are mutually contingent,and recur in response to the learning results achieved in the subsequent phases of innovation.This recursive model of the innovation process implies a long-term interaction between allthose involved in the innovative development work concerned.

The innovation process must not be comprehended as technology transfer pure and simple, inwhich knowledge production, application or utilization can be separated. Product or processdevelopment projects designed to culminate in series production and market success are de-pendent on overlaps and feedback with the research and invention activities inside and outsidethe company in question. Technology transfer is the abstract result of a complex process ofinteraction, with intensive feedback mechanisms on various levels.

In view of the economic importance of research work, and the high corporate interest in inno-vation projects and cooperative R&D jobs, it is increasingly vital to answer the question ofwhat factors impede innovating companies in their commitment to innovation, and which ofthese barriers to innovation can be broken down by accepting external knowledge, and byhaving the company cooperate with external academic or scientific institutions. The targetedprofitability of investment in R&D projects is highly dependent on technical implementation,the anticipated costs of the innovation process involved, and the chances of selling the productconcerned. Barriers to innovation inside and outside the company may restrict the planned ordesired extent of innovatory activity, or in extreme cases prevent it entirely. ZEW’s innova-tion survey has enabled us to distinguish between four categories of impediments to innova-tion:2

• implementation and sales risks

(1992), Nelson (1988), (1993), Nelson and Rosenberg (1993), Porter (1990), McKelvey (1993), Patel

and Pavitt (1994)

2 cf. Licht, Schnell and Stahl 1996 and see technical attachment

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• financing restrictions

• intra-company barriers

• legal formalities

Market-related risks constitute the most important obstacles for expansion of innovatory ac-tivity. However, these impediments (e.g. high costs and market risks) are not nearly so signifi-cant in the service sector as they are for the manufacturing industry; this is primarily attribut-able to the more buoyant turnover trends experienced in the service sector over recent years.Laws and legal formalities are seen by 25 (30) per cent of companies in the service sector(manufacturing sector) as a serious or very serious impediment to innovation.

Fig.: 1-2 Impediments to innovation in the manufacturing and service sectors

Implementation risk

Market risk

Cost risk

High innovation costs

Amortisation risk

Imitation risk

Lack of equity capital

Lack of outside capital

Lack of skilled workers

Lack of technical equipment

Lack of know how

Long approval procedure

Legislation and regulations

0% 10% 20% 30% 40% 50% 60%

Service sectors Manufacture sectors

Source: ZEW Mannheim Innovation Panel (1996), Mannheim Service Panel (1996)

At first glance, the impediments to innovation do not obviously signal the necessity for com-panies to cooperate with external researchers. Technical equipment and staffing would notappear to be bottleneck factors in this context. Furthermore, universities and other public fi-nanced R&D institutions are hardly suitable candidates for reducing companies’ capital andcost problems. The high significance of market and cost risks here, however, indicates thatdistributing the innovative efforts among several shoulders might indeed assist the companiesinvolved.

Many companies have probably hitherto underestimated the opportunities provided by coop-eration or in more general sense by using the national innovation system. In medium-sizefirms, particularly, restricted financial resources and the anticipated costs of an innovationproject dominate the potential benefits of other aspects so severely that the consequences ofisolation or inadequate integration in industrial networks are not sufficiently perceived. Com-panies display insufficient awareness of the interdependencies between financial resources,risk distribution and technological capabilities, and of the firm’s willingness to make a recep-

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tive commitment to inputs from outside. The consequence is that financial difficulties, the fearof costs and risks, and inadequate links to other protagonists in the innovation system, oftengo hand in hand with innovative weakness.

Institutions and their interrelationships have been shown to be a great importance for innova-tion and a element in diffusing Know-How as well as the source of mismatches and barriers.We should analyze the interface between universities, research institutes and transfer organi-zations based on surveys of business contacts and linkages. That means the incidence and va-riety of collaborations between industry and the science sector and the impact on the innova-tive performance of the business sector (OECD 1996 and 1997). In the following we willwork on

• a typology of the German institutional profile,

• some structural patterns of the German Business sector,

• firms innovation behavior in the national innovation system,

• the barriers to collaboration between the technological infrastructure and the firms.

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2 The institutional mapping of the German Innovation System

2.1 Main structure of the German System and its transfer channels

Theoretically, we should separate the actors of the innovation system into users of knowledgeand human capital, producers of knowledge and human capital, and transfer institutions. Sincewe talk about an innovation system and its complex interdependencies there is no clear overallassignment of the business sector as the user of knowledge which exploit it into commercialused innovation and the public sector and large firms as the producer of it. Furthermore, alltechnological and organizational innovations do have an impact on all aspects of the economy.Nevertheless, at this point we will assume that there is in a clear division in production ofknowledge and the transfer into commercial exploitable innovations.

The structure of a system in general is always path dependent in a way that traditions and his-torical issues set a base from where the system can move on. In this setting we don’t want togo deeply into the historical development of the university system and the conditions of thefoundation and growth of the independent research facilities during the last century. For now,the Federal structure of the society is the base of the institutional pattern of the German inno-vation system. Financing responsibilities for education, research, technological transfer, andinnovation performance are shared between the federal government, the state governments,and the private business sector. Out of this a variety of research institutions, universities andlabs was developed. The R&D performing and transferring institutions will be described moreintensively in section 2.3. We classified them by their financing resources depending on thefederal system of Germany. Besides universities and industry R&D facilities a variety of pub-lic and semipublic research institutions exists.

These institutions count for a large part of the technology transfer by direct or indirect transferto business sector enterprises. As elements of an innovation system which will be describedbelow they have a latent propensity to cooperate in innovative activities depending on certainconditions. However, there are deficits especially for small and medium size firms. Achieve-ments by public-sector research institutions fertilize industrial innovative success primarilyfrom three sectors: in the field of education and training, by increasing the human capital, bygenerating and publishing new knowledge from research work, and by direct support for com-panies in solving industrial problems within the framework of services. The channels there are

• R&D cooperation projects

• direct demand for applied research by industry enterprises, contract research

• consultancy

• personnel mobility

• education of practice-oriented capabilities in technical colleges

In addition to that there is a variety of institutions serving as intermediate facilities for transferactivities. Transfer institutions play an important integrating role in the diversified network of

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the German innovation system. It seems to be suitable to describe them at this point in moredetail.

There are three types of transfer institutions which are classified by the closeness to businessenterprises. First, there are mediators which are close to the industry. In many branches andindustries exist a chamber of the branch additionally a central chamber of commerce in almostevery large city in Germany. These chambers of firms of different branches are a good sourceof information on what types of knowledge and new technology will be important for the cer-tain industries. Another channel of technology transfer can be the associations of differentindustries that are actually mainly lobbies for interests than only technological knowledge.The second transfer channel is provided by independent technology mediators. To this groupbelong transfer agencies and information centers. One of the most effective institutions oftechnology transfer to small and start-up firms are the Centers of Technology and Firm estab-lishment. These centers are independent but get support from the chambers of commerce andin many cases from the city council. The third type of transfers institutions are closely linkedto research institutes or universities. This group contains university and transfer centers andthose of non-university research institutes. Testing, control and standardization facilities (e.g.TÜV) contribute by a considerable amount to the diffusion of knowledge from the researcherto the user. Institutionalized consultancy and independent development centers are also part ofthe transfer system.

Finally, some quantitative statements can tell a lot about the rank of research policy within thepublic interest. A huge amount of money and effort is spread over a wide system of R&D fa-cilities. The tables below show the rough composition of the science expenditures and theexpenditures on Research and Development by financing sources.

Table 2-1 Science expenditure of the Federal republic of Germany by financingsource

1993 1994 1995

absolute

in million

DM

in %

absolute

in million

DM

in %

absolute

in million

DM

in %

1. Government 51 082 50,4 52 446 51,0 54 956 51,8

1.1 Federal Government (incl. ERP) 20 372 20,1 19 950 19,4 20 688 19,5

1.2 Länder and local governments 30 609 30,2 32 496 31,6 34 268 32,3

1.3 Private Non-Profit organizations 1 622 1,6 1 645 1,6 1 591 1,5

2. Business enterprise sector 48 649 48,0 48 744 47,4 49 545 46,7

Total 101 353 100.0 102

836

100.0 106

094

100.0

Source: BMBF

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Table 2-2 R&D expenditure of the federal Republic of Germany by financing sectorand in % of GNP

1993 1994 1995

Financing sectors absolute

in million

DM

in % of

total R&D

expenditure

absolute

in million

DM

in % of

total R&D

expenditure

absolute

in million

DM

in % of

total R&D

expenditure

1. Federal Government 16 860 21,4 16 348 20,7 16 820 20,8

2. Länder 13 546 17,2 14 340 18,1 15 060 18,6

3. Business enterprise sector 48 023 61,0 48 090 60,8 48 900 60,3

4. Private non-profit sector 241 0,3 260 0,3 260 0,3

Total R&D expenditure 78 670 2,49* 79 038 2,39* 81 040 2,35*

* in % of GNP (gross national product)

Source: BMBF

In 1995 the total expenditures on R&D amount to 81 billion DM. That counts for 2.4 percentof gross domestic product. This is still a fraction that is comparable with the other highly de-veloped countries, though it has been declining during the last 5 years. As it is to be seen inTable 2-2 60.3 percent of total R&D expenditures are financed by the private sector and 39.7by the public sector. The expenditures of the latter are spent to two thirds at the federal leveland to one third at the state level. By the Basic Law of Germany the states are responsible foreducation policy. Therefore the main part of their R&D expenditures concentrates on the uni-versities. That means the focus is more on research and education than on technology, thoughthere are Technical Higher Education Schools who train mainly engineers with high techno-logical knowledge.

2.2 The business sector: Innovation and R&D activities

Since the late eighties, R&D activities in Germany have decreased significantly over theeconomy as a whole. This decline affects both R&D inputs and R&D outputs (measured as theproportion of R&D expenditure in GDP and in the number of patents of relevance for theglobal market).

However, the technical performance capabilities of a national economy are not solely deter-mined by the R&D activities involved; no less crucial is the ability to launch new or improvedproducts on the market, and/or to utilize new or improved production processes. This entailscosts above and beyond R&D pure and simple, e.g. for market analyses or staff training inconnection with new product launches. This paper will accordingly use the term "innovationactivity" in its wider sense as construed in the "Oslo Manual" (OECD, 1992).

That entrepreneurial decisions during the recession were primarily determined by cost consid-erations and profit trends, resulting in a backlog postponed for tackling until 1994, is alsomanifest in substantive decisions to conduct innovation activities irrespective of the expendi-ture levels involved. In 1993, for example, the proportion of product innovators fell and theproportion of process innovators rose. The pure product innovators in 1992 were predomi-

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nantly small firms employing fewer than 50 people. Since these companies generally sufferfrom a shortage of capital, only a small proportion of them could afford to invest in processinnovations; most of them discontinued their innovation activities.

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Table 2-3 Key variables on innovation behavior in the manufacturing sector (WestGermany)

1994 1993 1992

absolute in % absolute in % absolute in %

Enterprises 58 400 100 55 800 100 59 500 100

of which:

Innovators 31 100 53 100 30 500 54 100 36 700 62 100

of which:

Product innovators 27 900 48 90 27 100 49 89 32 700 55 89

Process innovators 25 200 43 81 25 800 46 85 26 000 44 71

R&D performing enterprises 22 900 39 74 15 800 28 52 21 400 36 58

R&D department 8 500 15 27 8 500 15 28 10 700 18 29

Sales (in billion DM) 1 880 100 1 856 100 1 997 100

of which:

Innovators 1 537 81.8 100 1 478 79.5 100 1 693 84.8 100

of which:

Product innovators 1 481 78.8 96.4 1 415 76.1 95.7 1 645 82.4 97.2

Process innovators 1 400 74.5 91.1 1 394 75.1 94.3 1 567 78.5 92.6

R&D performing enterprises 1 335 71.0 86.9 1 199 64.5 81.1 1 415 70.9 83.6

by type of product:

new or significantly improved 409 21.8 26.6 355 19.1 24.0 331 16.6 19.6

improved 361 19.2 23.5 375 20.2 25.4 424 21.2 25.0

unchanged or marginally changed 1 110 59.0 49.9*

1 126 60.7 50.6*

1 242 62.2 55.4*

Innovation expenditure (in billion DM) 73 3.9 4.8 75 4.0 5.1 93 4.7 5.5

of which:

current innovation expenditure 52 2.8 3.4 53 2.8 3.6 55 2.8 3.2

investments in innovation 21 1.1 1.4 22 1.2 1.5 38 1.9 2.3

of which:

R&D expenditure 55 2.9 3.6 57 3.1 3.9 55 2.8 3.3

Investments (in billion DM) 74 3.9 4.0* 85 4.5 4.7* 97 4.9 4.9*

Employees (in thousands) 6 472 100 6 869 100 7 491 100

of which:

Innovators 5 165 79.8 100 5 489 79.9 100 6 156 82.8 100

of which:

Product innovators 4 976 76.9 96.3 5 303 77.2 96.6 5 948 79.4 96.6

Process innovators 4 657 72.0 90.2 5 146 74.9 93.8 5 430 72.5 88.2

R&D performing enterprises 4 640 71.7 89.8 4 497 65.5 81.9 5 249 70.1 85.3

Source: ZEW (1996): Mannheim Innovation Panel

Notes: 1) Companies with at least five employees. 2) 1994 including start-ups from the years 1992 to 1994. 3) The propor-tion of innovators' sales accounted for by products unchanged or marginally changed, as a percentage of innovators' totalsales, and the proportion of innovators' investments as a percentage of innovators' total sales, are each marked with an *.

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The proportion of innovating firms among the total dropped by nine per cent. It subsumes theproportion of pure product innovators, of pure process innovators, and of companies imple-menting both product and process innovations, among the total of all companies involved.Since the absolute number of pure process innovators fell by only 800 firms between 1992and 1994, it is the decline in pure product innovators which is primarily responsible for thesmaller proportion of innovators in the overall total. In 1993 R&D activities were discontin-ued primarily by the smaller firms, whose R&D expenditure is infinitesimal compared withthe accumulated R&D expenditure of all the companies surveyed, but in the context of theindividual firms involved represents a far-from-negligible cost factor.

2.3 The German institutional profile

2.3.1 Introduction

Before describing the public institutional part of the German innovation system it is necessaryto motivate the activities of the public sector in undertaking and supporting research andknowledge transfer. The most important objective of governmental R&D and innovation pol-icy, both on a regional/national and international level, can be defined as to promote and pre-serve future corporate competitiveness. Additionally, the design of promotion programmesand institutions has to support the changing characteristics of innovation projects. In economicterms, external effects of corporate innovation activities have recently been adduced as a cen-tral justification for governmental intervention (for details, cf. Harhoff and König 1993 andKlodt 1995). The core argument here is that the national economic benefits of corporate re-search expenditure are higher than the benefits accruing to the individual company concerned.Thus in terms of the national economy as a whole, companies are not investing enough in dis-covering and developing new products and processes.

Another argument frequently adduced for governmental innovation subsidies involves theincompleteness of the capital markets. The task of research and technology policy in the senseof a second-best solution consists of mitigating the resultant financing restrictions on compa-nies for innovation projects. A series of specific programmes are based on this reasoning. Re-cent empirical studies indicate that companies are coming up against financing restrictions inregard to their innovation- and investment-related decisions (cf. Harhoff, Licht et al. 1996 andHarhoff 1996b). In the immediate context of the financing problem, reference is made tothreshold values for R&D activities, i.e. that R&D activities are perceived as efficient for thecompanies only after a defined minimum outlay has been exceeded. This is why various pro-motion programmes are advocated with the argument that the assistance is designed to com-pensate for size-entailed disadvantages (cf. e.g. EU 1996). In economic terms, this argumentdoes not appear per se to be adequate justification for specific assistance to small companies.Only in conjunction with market imperfections (e.g. on the capital market) can promotion becogently advocated by adducing R&D threshold values.3 Further economic arguments for

3 The empirical results presented in Felder, Licht, Stahl and Nerlinger (1995) indicate the existence of

threshold values in regard to the employment of R&D personnel, but not in regard to the R&D expendi-

tures as such.

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promoting R&D have been developed in the context of the new trade theory. Under purelyfree-enterprise control the existence of external effects and the implementation of returns toscale will prevent a social optimum being achieved. Selective intervention by the state wouldlead to welfare gains. This more specific promotion, however, requires detailed informationon the differing size of the externalities in the various sectors involved, which cannot be inter-nalized by "private strategies", such as cooperative endeavors in the R&D field.

The federal expenditures on R&D are mostly spent by Federal Ministry for Education, Sci-ence, Research and Technology (BMBF), the Federal Ministry of Defense (BMVg) and theFederal Ministry of Economics (BMWi). Among these ministries the BMBF has the mostimportant part in financing R&D. As a coordination advice the Science Council at the Federaladvises the government in research policy and integrates the state activities with federal ef-forts to support activities in the innovation system.

The direction of support by the BMBF can be regarded in four main areas:

• support of institutions and organizations undertaking R&D

• support of R&D projects in the business enterprise sector (direct and indirect)

• financing the support for special areas of research independent from the institution or firmwhere it is or will be undertaken

• financing the Expansion and Construction of Universities, building an Infra structure

These focus points of research support are overlapping and complementary at the same time.Some of the projects and programs are implemented in the research activities of institutes thatcan be more or less linked to the government. The cooperation relations and organizationallinkages among the research facilities are complex and very flexible.

2.3.2 Promotion organizations mainly project support

2.3.2.1 DFG (German Research Council, Deutsche Forschungsgemeinschaft)

promoted jointly by the federal and state governments

is the major promoting organization and self-government for science and research activities inGermany. One of its main tasks is the financial support of research projects, supporting re-search cooperation and promoting young scientists. Secondly, it is an important consultant forpolicy maker in terms of scientific questions. Thirdly, the DFG develops and keeps the rela-tionship and cooperation with international research institutions.

There are formal structures and instruments such as, postgraduate and postdoctoral programs,launching special research areas and supporting teams of researcher of different institutionsand fields of interest. The DFG is financed by both the federal and the states.

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2.3.2.2 DAAD (German Academic Exchange Service, Deutscher Akademischer

Austauschdienst)

is the organization which supports and organizes exchange programs for students, post-graduate and post-doctoral researchers with foreign universities and research institutes. TheDAAD is a common institution of the universities and mainly financed by the office of for-eign affairs, the ministry of Education, Science, Research, and Technology (BMBF), and bysome of the foreign cooperation partners. The main instruments are scholarships for and fi-nancial support of exchange students and researchers as well as the organization of the admin-istrative formalities. Additionally, it provides information on foreign research programs, uni-versities, teaching opportunities and so on.

2.3.2.3 Alexander von Humboldt foundation (AvH)

promotes foreign scientists and researchers. It was founded and is mainly financed by the of-fice of foreign affairs and the ministry of Education, Science, Research, and Technology.There are programs launched by the AvH which support cooperative research projects bet-ween Germany and other countries. Additionally, scholarships and prizes for academics werefound.

2.3.2.4 Stifterverband

is an association of firms, different private non-profit organizations and private persons. Itsupports science and technology projects as well as institutes or other organizations whichneed additional financial or organizational help to perform R&D. The Stifterverband providesservices such as statistics of economic indicators, seminars, infrastructure facilities for scien-tific activities.

2.3.2.5 Volkswagen-Foundation (VW-Stiftung)

has three main tasks: 1) promotion of basic research in special fields, 2) improving the infra-structure for research, teaching, and scientific communication, 3) promotion of research ori-ented towards cooperation with foreign countries. Only institutions can be supported by theVW-Foundation and only for a limited time. It was founded by the state Lower Saxony andthe Federal. The financing support comes from dividends of Volkswagen AG shares the stateLower Saxony owns and from the foundation fortune.

2.3.2.6 German Federal Foundation of Environment (Deutsche Bundesstiftung

Umwelt, BDU)

supports applied research and innovations in the field of environmental protection with a spe-cial focus on medium sized firm. A main task is the transfer of knowledge on environmentalprotection and technological Know-How related to it. It is an private foundation financed byrevenues form the fortune and the salaries of a firm owned by the Federal.

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2.3.2.7 CAESAR (Center of Advanced European Studies and Research)

This foundation mainly paid by the federal has no special area of research but it is orientedtowards research and development of new technologies. A research center in Bonn undertakesa combination of basic and applied research in the field of technology and natural science.

2.3.2.8 Arbeitsgemeinschaft industrieller Forschungsvereinigungen (AiF)

assembles more than 100 industry research organizations. AiF promotes applied research anddevelopment mainly to support small and medium sized firms. Since this organization keeps aspirit of community and common interest, the activities are focused on industries andbranches. It receives joint funding from the federal ministry of economics and industry.

2.3.3 Supporting organizations mainly on institutional support.

2.3.3.1 Max-Planck Gesellschaft (MPG) promoted jointly by the federal and state

governments

The Max-Planck-Gesellschaft zur Förderung der Wissenschaften e.V. is a sponsoring organi-zation with 71 research facilities, being active and spread all over Germany. 27 research insti-tutes out of the 71 institutes are active in the new Laender. The MPG is mainly engaged inbasic research in selected areas of the natural science, social science as well as arts. The soci-ety picks up especially new, promising research topics which do not have yet an adequateposition at universities. The MPG cooperate with universities and provides them with theirmajor appliances. The expenditures of 1994 amount to 1616 million DM and for the year1995 to 1708 million DM. The MPG employed 11500 employees, among them 3015 scien-tists.

2.3.3.2 Fraunhofer society (FhG) promoted jointly by the federal and state

governments

The FhG is a sponsoring non-profit organization with 47 facilities for applied research andtwo service facilities in 14 Laender. 10 of them are located in the new Laender (in 1995).Additionally, there are three further offices in the USA. Carrying out contract research proj-ects for the business and the public sector, the FhG contributes to transfer results of the basicresearch in practice. The institutional promotion by the federal government and the Laenderenables the FhG to handle self-chosen research topics for securing their scientific potentialand the development of new technologies resp. their constant observation. The FhG offersfirms and public authorities its services in the area of:

− microelectronics

− information technology,

− production automatization,

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− production technology,

− material and components,

− process engineering,

− energy and structural engineering,

− environment and health

− technical-economic studies and professional information.

The close relationship to universities is institutionalized through the joint appointment ofFraunhofer directors as regular university professors.

2.3.3.3 National research centers or Helmholtz-Centers promoted jointly by

the federal and state governments

These centers, as the most of the other research facilities, are mainly financed by the federalgovernment and especially by the BMBF. Research using large-scale equipment with a fo-cused on specific priority topics primarily large accelerators, neutron and synchroton sources,as well as observatories and telescopes is the special aim of Helmholtz-Centers. There are 16of them in Germany. In own projects and as partners for universities and other research insti-tutes the Helmholtz-Centers contribute significantly to long-term basic research in severalfields of natural sciences.

2.3.3.4 Institutions on the „Blue List“ promoted jointly by the federal and state

governments

Next to the major research facilities of the Max-Planck-Gesellschaft and the Fraunhofer-Gesellschaft, the federal government and the Laender can promote together research facilitiesand facilities with a service function. The " Blue List " contains more than 80 facilities whichbelong to the „Blue List“. Within the wake of the German reunification and the following set-up of a new overall German research "landscape", the " Blue List " has been expanded to 34institutes in the new Laender from 1992 onwards. The " Blue List " is characterized as one ofthe four mainstays of the common promotion of research of the federal government and theLaender. It covers all major sections of natural and social sciences, technology and appliedtechnological researches. An independent science council evaluates the Blue-List-institutionsin certain intervals whether they meet the criteria of scientific work.

2.3.4 Federal institutions performing R&D

Most closely linked to the federal government are the Departmental Research Institutes. Theirresearch is aimed at obtaining scientific findings which are directly related to the field of ac-tivity of a ministry. Such findings are used as a basis for decision making to ensure properexecution of departmental functions such as security and military problems, public transporta-

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tion, and standards. 56 Federal institutions performing R&D exist and they are lead by Areasof Responsibility of the ministries, of the Federal Chancellery, and the Office of Foreign Af-fairs. These facilities are fully funded by the federal. A variety of technical and scientific li-braries and information centers belong also to these Areas of Responsibility and therefore theyare a part of the knowledge transformation system as well.

2.3.5 University related special programs

The only exclusive responsibility of the states is the education policy. Therefore higher edu-cation belongs to this field. Even though, in order to keep an attractive environment for re-search and innovation the Federal supports the building and extension of higher educationinstitutions. In addition, there are special programs conducted by the Federal Government forlimited periods of time in agreement with the state governments in order to support universi-ties in fields which require rapid and disproportionately high funding. These special programsare of use both to teaching and to research and contain postgraduate and postdoctoral pro-grams as well as special research programs.

2.3.6 Universities

In 1995 exist in Germany 113 universities, 46 universities of art, 167 academies, such asTechnical Higher Education Schools. The latter are focused on education and technical skillsrather than on theory and research.

About ¾ of all 1.9 million students are enrolled at universities, 25% at academies. The budgetfor teaching and research is estimated by about 33.7 billions DM in 1995. The expendituresfor research and development amount to 14.9 billions DM (estimated).

The natural sciences received 3.9 billions DM, followed by expenditures for medicine (3.7billions DM). The budget for the social sciences amounts to 2.7 billions DM in 1995. In Ger-many universities are financed at the federal level and by the Laender. Besides the promotionof industry increases steadily to 4.6 billions DM in 1995. In 1993 there are 110.000 employees(full time equivalents) for R&D. This is about 1/3 of the university staff.

The organizational structure of German universities is important for an understanding of theresearch and transfer system. The major bodies in charge of the distribution of institutionalfunds for teaching and research are the various schools (faculties). Theses schools comprise anumber of chairs responsible for different areas of teaching. Several chairs often establishinstitutes (An institutes) where the professors organize research on their own behalf. Thestatus of theses institutes varies widely from completely independent institutes to closelylinked ones. Often the An institutes’ research is financed and performed jointly with the pro-moting organizations.

A summary of the financial sources, size and main research areas of the institutions describedabove is to be seen in table 2-4. Additionally, figure 2-2 gives an orientation on the financialstructure of the institutional system of research and innovation in Germany.

18

Figure 2-1

Main structure of the Institutions of the G

erman Innovation S

ystem

research facilities

supporting organisationprom

oting organisations

HG

F

Industry

Foun

dations ( AvH

, DA

AD

, CA

ES

AR

... )D

FG

FhG

MP

G

Blue list

AiF

Institutes

other institutes

MP

G

Institutes

Industrial and private laboratories

FhG

Institutes

National

Research C

enters

Depart.

research institutes

States

Fede

ral m

inistries ( B

MB

F, B

MW

i, BM

Vg, ... )

AiF

Universities

Science coun

cil

19

Table 2-4 Financial resources and main areas of activity of German research insti-tutions

Institution Expenditure

DM million

Public

support

DM

million

Number

of Insti-

tutsEmplo-

yees

Public sup-

port DM

million

Relation of

support

federal /

states

Main area of research

DFG 1 927 1 147 1 147 100/0 Physics 21,3 %

Biology 31,7 %

DAAD 372,6 354 1 354 90/10 exchange of stu-

dents & scientists

AvH 87,7 87,7 78 87,7 100/0

Stifterverband 141,7 foun-

dation

wealth

foundation

wealth

Volkswagen-Foundation

113 founda

tion

wealth,

divi-

dends

93 foundation

wealth,

dividends

DBU 150 founda

tion

wealth

87 foundation

wealth

CAESAR 750 685 685

AiF 170 107 170 100/0

MPG 1 533 1

429,9

98 11

901

1 429,9 50/50 Physics 21,3 %

Biology 31,7 %

FhG 1 261 578 49 6 099 578 90/10 2

Engineering sciences

72%

Helmholtz-Centers

4 171 2 900 16 22 501 2 900 90/10 Natural sciences 67%


25%

„Blue List“ 1 321 1 200 83 10 000 1 200 50/50

Federal Institu-tions

2 867 2 867 57 18 682 2 867 100/0 Natural sciences 34%


29%

Agricultural science

14%

Source: BMBF

1 Contains 27 Mio DM from the EU.

2 The 10 % of funding outside the Federal comes 1:9 from the Laender and from the EU.

21

2.4 Firms using the German national innovation system

2.4.1 Introduction

Empirical studies lead to the conclusion that countries differ in the way in which knowledgeflows and that innovation takes place in a specific national context. The importance of thenational framework according to firms needs and wants is not independent from the countriessize, the size categories of the firms, the firms industry status, and the technology. In order toimprove the understanding of innovation behavior and technology transfer in the German na-tional innovation system from the firms point of view we try to answer the following ques-tions:4

• Which kind of mechanism do firms use to acquire and transfer technological Know-How?

• Which sources of information do stimulate innovation ideas and activities?

• Who are firms favorable partners for R&D-co-operation?

• How significant is co-operative R&D for business success?

• To what extent are firms involved in R&D-promotion programs?

On the base of some theoretical comments and empirical findings we will discuss how a na-tional innovation system works, how firms use the system as well as promotion programsgiven by different sponsors, and how a matching of the public support and a focusing of firmsspecific demands could contribute to a more efficient R&D policy. The discussion will dealwith flows of technology and information among people and institutions and might lead to abetter understanding of knowledge generation, diffusion and adaptation within a national in-novation web.5

2.4.2 Technology transfer mechanisms and sources of information

It must be stressed from the very beginning that technology transfer subsumes more than con-tract research, and that the conditions under which contract research is effective cannot alwaysbe separated from the effects of other technology transfer modes. In many cases, it is not tech-nologies or products which are transferred, but knowledge, enabling companies to developmarket-driven innovations themselves in-house, thus expanding their own innovative poten-tial. Support for companies by transfer of new knowledge can be implemented through vari-ous channels:

4 The data sources are described in the technical attachment. The empirical base dates from 1993 and will

be updated until the end of the project with data taken from the fourth survey 1996.

5 See also Arundel et al. 1995, Beise et al. 1995, Harhoff and Licht et al. 1996, Licht 1994.

22

Figure 2-2 Technology transfer mechanisms in the manufacturing

0 10 20 30 40 50 60 70 80

Joint ventures

enterprise

Purchase of another

Licences etc.

contracted out

Results of R&D

services

Use of consultancy

of equipment

Purchase

people

Hiring skilled

InformalCommunication

Share of the companies (%)

national

international

Big companies

SMEs

Source: ZEW Mannheim Innovation Panel (1996)

Interchange of Know-How is for more than 40 per cent of medium-size companies in themanufacturing sector an important transfer mechanism, and indeed the most important whencompared to other channels. More than 70 per cent of big companies are transferring Know-How by using informal communication and informal outside contacts. Almost 40 per cent ofthe small and medium-size companies obtained technical knowledge by acquiring machineryand equipment. The hiring of qualified staff was the second-commonest technology transfermechanism cited by all companies, followed by the purchase of equipment and the use of con-sultancy services.

In general, the engagement of firms with more than 500 employees is more intensive as it is insmall and medium sized firms. Big companies are involved to a higher extent in internationalbusiness. But both size categories of enterprises show a similar ranking. In conclusion jointventures, purchase of licenses or patents are relative important international transfer mecha-nisms, whereas the purchase of another enterprise, hiring skilled people and the use of consul-tancy services is more suitable in a national context.

As much important as the different transfer channels of new knowledge are the numbers ofvarious information sources that firms use to come in touch with fruitful ideas. Some sourcesare closer to the market, e.g. suppliers, customers or competitions, than other, that are morerelated to the science field like universities or private or government R&D labs. More than 80per cent of innovative firms see customers as an important or as the most important source ofinformation useful for their own innovation activities. Suppliers rank on the second place. Thedemand pull seems to be far more important than the technology push both to big companiesand to SMEs.

But, when compared to other information sources like private or government labs or technol-ogy transfer centers. Universities are the most important information source, that firms use to

23

get research based informations. Government labs like Fraunhofer institutions or Max-Planckresearch centers and the technology transfer centers falling behind universities and technicalcolleges. Again, the importance of fairs or exhibitions is a clear hint for the role that informalcommunication play in a national system of innovation.

Figure 2-3 The importance of sources of information6

Professional journals

Fairs, exhibitions

Patents

Technology transfer centres

Government labs

Universities

Private R&D labs

Consultants

Competitors

Customers

Supplier (equipment)

Supplier (intermediate goods)

0% 10% 20% 30% 40% 50% 60% 70% 80% 90%

SMEs

Big firms

Share of companies (%)


The significance of universities as sources of information for corporate innovations might bean indicator for the relevance of university-based research for the company’s product groupingor production processes. Thus the significance of academic knowledge from research institu-tions for corporate research facilities is also highly correlated to the latter receptiveness tocooperation as such.

2.4.3 Firms cooperation behavior

Studies on technology transfer not only between the academic and business communities butalso related to inter firm collaborations regularly reveal that a substantial part of existing tech-nology transfer in the German innovation system is self-organized, and takes place directlybetween scientists and corporate technicians or managers. Cooperative projects both betweenthe science sector and the industry and inter firm collaborations are the most effective form ofknowledge and technology transfer.

6 In the following graphs ‘private R&D labs or institutions’ label institutions of the Arbeitsgemeinschaft

Industrieller Gemeinschaftsforschung; ‘government labs’ stand for Fraunhofer society, Max-Planck-

Gesellschaft, Helmoltz-Zentren; ‘technology transfer centers’ summarize the variety of transfer agents

and information centers at the universities, technical colleges, Industrie- und Handelskammern (IHK)

and others.

24

Cooperative research projects are usually conditional on ongoing R&D activities at the com-panies involved. The cooperation partner can always contribute only complementary knowl-edge. In the case of cooperative projects with public-sector research institutions in particular,companies cannot outsource the necessity to design market-driven product/process innova-tions. Universities and public-sector institutions, remote as they are from the marketplace, areof limited suitability for developing finished products for the actual market. Some empiricalfindings are worth to mention:

• Cooperative projects presuppose in-house capabilities, and evolve complementary syner-gies.

• Geographically apportioned obligations are rendered obsolete: the partners interchangetheir roles.

• The foundation is personal experience and mutual trust.

• Transfer is made directly; institutionalization is possible and desired only to a very slightextent.

Figure 2-4 Proportion of companies with cooperation projects

0 5 10 15 20 25 30 35 40 45

Competitors

Private researchinstitutions

Government laboratories

Suppliers

Clients, customers

Universities

Share of cooperat ing com panies in percent

5-49 50-499 500 minimum


45 per cent of cooperating companies from the manufacturing sector employing more than500 people cooperate with universities. Here, universities are the cooperation partner numberone followed by horizontal or vertical interactions with clients, suppliers or government labo-ratories. For innovative small and medium sized enterprises clients and customers are themost preferable partners. It is obvious that these firms cooperate on a lower level with institu-tions in the science sector such as private or government research institutions. The integrationin the innovation system is not that deep.

So, cooperation is an indicator to measure firms ability and willingness to be an insider of thenational innovation system and vice versa the lack of integration and an outsider position.

25

Empirical analysis reveals that the probability of small and medium sized companies cooperat-ing with a university rises (Beise et al. 1995, Beise and Spielkamp 1996)7

• the larger the company is in terms of payroll,

• the higher the company’s R&D personnel intensity is8,

• the higher the significance of universities as sources of information,

• the less the company sees its innovations as easy to imitate,

• when the CEO has a doctorate.

Fig. shows a steep rise in the proportion of cooperation projects shared between companiesand universities as the company size increases. This size-related effect is highly significant inthe case of university-related cooperation. When it comes to cooperative projects with publicand private-sector research institutions, the size effect is less marked.

The greater affinity of large companies with universities is also transferred to their small andmedium-size subsidiaries: subsidiaries of large companies are more likely to cooperate withuniversities than are independent medium-size companies of equal size. In-house innovativeactivities, expressed in R&D or innovation intensity, increase the likelihood of companiescooperating with universities. Usually, cooperative R&D projects with the R&D departmentare not suitable for compensating or replacing deficits in small companies’ innovatory efforts.It has emerged that cooperative R&D projects, especially when small companies are involved,are as a rule complementary and not substitutional to in-house R&D activities. They shouldnot be comprehended as make-or-buy decisions.

7 See technical attachment

8 The R&D personnel intensity is the quotient of the number of R&D employees and the total payroll.

26

Figure 2-5 Proportion of companies with cooperation projects

0% 5% 10% 15% 20% 25% 30%

Universities

Clients, customers

Suppliers

Government laboratories

Other firms within group

Competitors

others

R&D-intensive sectors

Share of companies (%)


Almost 10 per cent of cooperating companies from the R&D-intensive categories (chemicals,mechanical engineering, car-making, electrical engineering) of the manufacturing sector co-operate with competitors. Most of the companies - without respect to the firm size - cooperatewith universities. On the second place there are the clients and customers.

These results might be interpreted as a signal thus cooperation is able to compensate for cor-porate R&D shortfalls only to a limited extent. It would be truer to say that it gives companiesthe complementary academic support for their own innovatory efforts. The ability to adaptexternal technical knowledge from research institutions is conditional on an in-house corpo-rate innovatory potential. This because of the manufacturing maturity for new products andprocesses can be achieved only on the spot, i.e. in the company itself. And, cooperation willfrequently not lead to a prototype straight away. On the contrary, what is being transferred isknowledge, enabling the product concerned to be developed in the company involved.

Companies which see a major impediment to innovation in the fact that their new products ornewly developed processes are quickly imitated by competitors, are inclined to hold backwhen considering whether to cooperate with universities in research projects. Here the obser-vation is confirmed that companies which are concerned about a Know-How drain to thecompetitor will seek to implement their innovatory development work preferably without in-volving public-sector research institutions and universities as partners. This concern is de-scribed in two aspects:

• Firstly, a company usually has to input its own Know-How into a cooperative project. Forexample, in order to improve a manufacturing process, the technology used hitherto mustbe revealed in its entirety to the outside scientists involved. Since process innovations are

27

often not protected by industrial property rights, there is a risk that these scientists maypass on the knowledge concerned.

• Secondly, the results of a cooperative research project are shared among all the participantsinvolved, so that here, too, dissemination of the newly created knowledge by the partners isa real possibility. Even if industrial property rights have been applied for or secrecy hasbeen imposed by contractual obligation, enforcing one’s rights after a violation of the con-tract will be a time-consuming and costly exercise for a medium-size company.

On the part of academics, the qualifications of the corporate employees involved are oftendesignated as crucial for effective cooperation in R&D matters. In addition, the personal atti-tude of corporate management in relation to academic institutions, particularly universities,will affect the readiness or ability to cooperate with universities in research projects. It hasemerged that companies headed by CEOs with a doctorate are, ceteris paribus, more likely tocooperate with academic institutions:

2.4.4 Firm’s involvement in R&D-promotion programs9

Discussions on firms integration in the German innovation system by analyzing transfermechanisms, informations sources and the cooperation behavior are focusing on the quality orusefulness of the R&D infrastructure. In addition to the importance of the innovation frame-work the impact of direct support of firms involved in R&D is a crucial topic. The dissemina-tion of R&D promotion can be regarded as a somewhat ad hoc success indicator of the R&Dpolicy. Even though it is a poorly measured variable it can give some hints regarding the tar-get groups of different programmes and the direct support to firms in the German nationalinnovation system given by different sponsors.

Promotion programmes also aim to eliminate shortfalls in corporate innovation activity. Boththe German federal government and several of the Laender, for example, operate promotionprogrammes designed to counter the lack of financial resources which many small and me-dium-sized enterprises see as the central impediment to innovation. Other programmes aim tostrengthen the qualification basis for innovation activities. This leads to the question to whatextent firms participate and gain from R&D- promotion programs.

Some results from an analysis of the Mannheim Innovation Panel are discussed below. Largeenterprises participate in promotion programmes more frequently in relative terms than dosmall and medium-sized enterprises, as shown in Fig. Among SMEs there is also a lesserprobability of their taking part in R&D promotion programmes of the EU.

9 This part is a brief summary of Chapter 5 taken from Licht, Schnell and Stahl (1996)

28

Figure 2-6 Participation in promotion programmes during the years 1992 - 1994 byfirm size

0% 5% 10 % 15 % 20 % 25 % 30 % 35 %

P ro m o te d firm s

F irm s p rom ote d by fed era lgo vernm ent p rogra m m e s

F irm s p rom ote d by La en de rp ro gram m e s

F irm s p rom ote d by E Upro gram m e s

P ro p o rtio n o f R & D p e rfo rm in g firm s ( in % )

S M E s

La rge com pan ies

Source: ZEW (1996): Mannheim Innovation Panel

The differentiation in research programme sponsors reveals that in total the research pro-grammes of the German federal government are considerably more widely disseminated thanR&D programmes operated by the Laender and the European union. Research programmesrun by the German federal government are utilized more frequently by companies in the east-ern Laender than in the west of the country. When participation in promotion programmes isexamined separately for the west and east of Germany, the relative proportion of companies inthe east of the country is clearly preponderant. Additionally, the differences in participation ofEast German firms differ dramatically in respect to size and intern R&D intensity from WestGerman firms. That can be partly explained by additional R&D and economic policy instru-ments for the New Laender such as subsidies and tax advantages.

A disproportionately large number of top-tech, High-Tech and technical service companiestake part in the German federal government's promotion programmes compared to companiesfrom other sectors. The technical service companies are the pacesetters here, followed by thetop-tech and High-Tech sectors.

Deeply statistically investigations have been carried out separately for firms in the west andthe east of Germany. During these turned out that there is a definite statistical correlation be-tween the importance of the anti-innovation factor "lack of loan or equity capital" and the par-ticipation in promotion programmes operated by the Laender: promotion programmes offeredon a Laender level are (following checks for sectors, company size, sales trends and humancapital in top management) more widely disseminated among those companies which com-plain about lack of capital. Promotion programmes are significantly less widely disseminatedamong companies where the fear of imitators is particularly pronounced.

29

German federal government programmes and EU programmes are therefore frequently ad-dressing the same clientele. Therefore it is becoming increasingly urgent for the German fed-eral government and the EU to coordinate their activities more effectively, so as to precludeany further growth in the existent multiplicity of promotion programmes, entailing as it doessubstantial costs for private companies in selecting the appropriate programmes, with con-comitantly adverse effects on efficient goal achievement in the economy as a whole.

The allocation of promoting resources could aim towards shifting the promotion of commer-cial-scale systems or new technologies more onto the EU level. In these development only asmall number of companies in the entire EU are involved. Promotional measures which aimfor a broadly based effect would have to be relocated more on the national or regional level.Promotion programmes on the part of the SMEs are already being targeted on the nationallevel. This is particularly necessary when we remember that the information costs incurred byprivate companies for promotion application and implementation will increase the morecomplex and long-winded the selection procedure and the programme multiplicity involvedhave become.

2.5 Implications

As the results of a quantitative investigation of the German innovation system and especiallyof the transfer system reveal, promoting programmes and facilities have to be adjusted to theneeds of firms. This is true especially when these firms do not have a sufficient performancedue a lack of innovation. The variety of institutions classified as ‘producers’ of technicalknowledge might be interpreted as a reflex to the heterogeneity of the firms. Therefore, anefficient technology transfer or national innovation system must be flexible and decentralized.

At the firm level different needs and wants are obvious. Big companies use the innovationsystem more intensively than SMEs. This is valid for all forms of Know-How transfer aretaken into account. Technology transfer here is a strategic function and belongs to the generalinformation management. In contrast small and medium sized firms prefer informal commu-nication with local actors, they are looking for personnel contacts and like to be independent,they act spontaneously and often on an operative level.

In general, any kind of technology transfer or collaboration among firms or between the busi-ness sector and research institutions is based on trust and experience. The social interweave-ment of the academic and business communities is a crucial factor. Direct contacts and infor-mal networks form the primary channels for transmitting scientific findings and technicalknowledge within the innovation system. Therefore a flexible, decentralized and deregulatedpractice of technology transfer promotion can most effectively contribute to establishing andstabilizing these informal networks.

Surprisingly enough, the innovation survey reveals that medium-size companies which com-plain of inadequate in-house or outside capital for financing their innovations exhibit no lesserwillingness to cooperate with universities than do companies which see financing problems asless of an impediment to innovation. Thus the readiness to make a financial commitment tocooperative projects does not depend on financial restrictions. It is truer to say that confidenceand experience lead to different corporate risk structures. Cooperating companies confirm that

30

the financing costs are only one aspect out of many which are weighted and relativized withinthe context of the targeted innovation result.

Cooperating companies see a close correlation between cooperating (with universities) andcorporate success. In this they differ from companies which are interested in starting their firstcooperative project, but wish to begin with only a relatively small budget. The reason behindthis hesitancy on the part of companies fundamentally interested in cooperation is thus not abasic liquidity weakness. It is truer to say that the company’s risk is increased during a firstcooperative project by the uncertainty surrounding the procedures involved and the chances ofsuccess, plus as-yet-not-established confidence in the partner concerned. This constitutes aninhibitory threshold, which has to be overcome by companies which have not yet cooperatedwith academic institutions, if they are to utilize effectively technology transfer from these fa-cilities on a long-term basis.

There remains uncertainty as to what politicians can in the final analysis improve technologytransfer. Of course, there is no lack of suggestions on how technology transfer could actuallybe enhanced, but it has to be accepted that not all companies participate equally in technologytransfer:

• An effective technology transfer policy thus does not replace R&D sponsoring for smalland medium-size companies, but supplements it. It has also emerged that the initial com-mencement of R&D activities constitutes the main inhibitory obstacle for small companies.What could be termed “threshold sponsoring”, i.e. assistance primarily for companies notyet operating their own R&D activities, will expand the group of companies eligible forcooperative R&D projects with public-sector research institutions.

• Market mechanisms as traditionally comprehended would appear of limited usefulness forcoordinating the transfer of knowledge and technologies. Pure market systems are found innone of the environments inhabited by public-sector research, neither in the labour marketfor researchers, nor in R&D contracts and engineering services. Assigning an a prioristatus to the market process thus bypasses the core of successful technology transfer in theresearch field. Promotion of technology transfer should not aim to compensate for the mar-ket’s putative failures, but should help to overcome the problem of knowledge diffusion atthe boundary between basic research and development phases in the innovative process.

• One significant factor in this context is the positive correlation between cooperation prob-ability and the importance of universities as a source of information for companies. If theuniversities succeed in drawing companies’ attention to the research and transfer potentialsthrough an industry-friendly communicative approach, then the first and vital step has beentaken towards potentially fruitful cooperation.

• Enhanced incentives for the academics not yet cooperating can be achieved by linking ad-ditional financing to cooperation with companies, or by a bonus system for technologytransfer projects. Compared to free publication of research results accessible to all compa-nies, intensified cooperation is a longer-term process of development.

To increase the efficiency of technology transfer, the usual recommendation is to establishadditional institutions designed to act in a mediation capacity between research institutions

31

and companies. In a similar way to the employment exchanges in the labour market, the ideais to “place” the outsiders in technology transfer with the appropriate academics, and to com-pensate for any entrepreneurial shortfalls in project and innovation management. The crucialfactor then will be maximally synergized cooperation between these institutions, justifying theappellation of an institutional network. This institutionalization is fundamentally aimed atinvolving the research facilities in business promotion, even though it primarily attempts tocompensate for management shortfalls in the companies. Since this management Know-Howis not available in the research institutions, third parties will have to contribute this knowl-edge.

By comparison, concentration on the core question, of how new research results can succeedin finding their way into companies (i.e. actual applications), would not basically require insti-tutionalized support. On the contrary, empirical feedback from successful technology transfersdemonstrates the importance of self-organization by innovative companies and technology-driven new businesses. The bottleneck of technology transfer in individual fields of technol-ogy then primarily lies in the small number of insiders really involved in the national innova-tion system. Effective promotion of technology transfer should thus aim at establishing long-term cooperative relationships between companies and between companies and academics.

32

3 Attachments

3.1 ZEW’s data sources utilized

Mannheim Innovation Panel (MIP): the MIP contains a random sample of manufacturing-sector companies in the west and east of reunified Germany. At the request of the GermanFederal Ministry for Education, Science, Research and Technology (BMBF), ZEW has since1993 conducted an annual survey to analyze corporate behavior patterns in an innovationcontext. About 3000 companies took part in the representative surveys conducted in 1993and 1994. Besides various structural questions concerning the company itself, its innovationexpenditure and R&D activities (these questions are retained throughout the entire survey du-ration), specific questions are posed as well:

• In the first wave back in 1993, questions were put on the acquisition and dissemination oftechnical knowledge, the sources of information, the innovatory goals, and the impedi-ments seen to innovation as such. This survey was part of the Community Innovation Sur-vey (CIS 1).

• The second survey wave in 1994 contains specifically focused questioning on forms ofcooperation adopted by manufacturer and supplier, changes in vertical business relation-ships, and on fields of technology where R&D activities were currently ongoing, and prod-ucts/processes being developed.

• The third survey was begun in March 1995. Special topics in this year were impediments toinnovation, and human capital.

• In the fourth survey, held in 1996, questions were once again put concerning the acquisi-tion and dissemination of technical knowledge, sources of information and innovationgoals. These were supplemented by a survey on R&D expenditure and cooperative R&Dprojects, plus questions on innovation and the environment.

• The fifth wave is in the field. Again, this survey is part of the Community Innovation Sur-vey (CIS 2).

Service Panel (MDP): this representative survey was then used to obtain data on the use ofnew technologies in the service sector and on the creation and introduction of new services.The companies of the various service categories have been surveyed annually since 1995 forthis purpose.

ZEW’s East German Company Panel: this file contains approx. 620,000 companies in theeastern provinces of reunified Germany. In addition to data on corporate structure, it alsosupplies a lot more information, e.g. on share-holdings, establishment dates and corporatesuccess. This panel can be interlinked with the MIP using a company code number.

33

3.2 Probability model of cooperation

The analyses are based on linear regression and heteroscedastically ordered probit models.

• Table 1 shows the impact of firms cooperation with an university on the performance of theenterprise measured by the proportion of new or significantly improved products.

• Table 2 shows the results from three probit model versions testing the impact of the readi-ness to cooperate.

In contrast to linear regressions, the coefficients of the probit models cannot be interpreteddirectly; here, however, the sign, the significance and (in the case of dummy variables) thecomparison between the coefficients are relevant for interpretation. The statistical significanceof the estimated coefficients is designated by the number of asterisks. In this context, (*), (**),and (***) mean significant with an error probability of 10 (5) and (1) per cent.

Table 3-1 Proportion of new or significantly improved products

Linear Regression-Model I II III

Number of observationsAdjusted R2

N= 6810,10

N= 6330,10

N= 5780,13

Company sizefewer than 50 employeesbetween 50 and 250Basis: 250 to 500

2,822,67

3,772,85

3,512,33

Proportion of R&D staffup to 2.5 %between 2,5 and 5 %more than 5 %Basis: no research

3,536,41*17,36***

3,026,11*16,75***

2,917,46*16,53***

CEO’s educationDoctorateUniversity degreeMaster craftspersonBasis: other

0,63-2,3311,63*

3,31-0,4114,67**

Subsidiary -0,98 -1,24 0,15Cooperation withUniversitiesTechnical/scientific institutesPrivate research centers

7,34**-0,52-5,30

7,81**-1,32-6,76

Impediments to innovationInnovations too easy to copyInsufficient financial resourcesLack of technical equipment

3,03**-3,42**-4,48***

34

Table 3-2 : Co-operative projects with universities

Probit models I II III

Number of observationsPseudo R2

N= 8700,17

N= 7790,29

N=7500,32


-0,82***-0,37***

-0,68***-0,34**

-0,62***-0,32**


0,290,74***1,07***

0,190,68***0,88***

0,190,74***0,98***


0,45*** 0,40**-0,09

0,49***0,07-0,69

Subsidiary 0,27** 0,38*** 0,31**Importance as source of informa-tionUniversitiesTechnical/scientific institutes

0,65*** 0,72***

Impediments to innovationInnovations too easy to copyInsufficient financial resources

-0,29***0,03

35

Table 3-3: Co-operative projects with public research institutions

Probit -Modelle I II III


N= 8330,16

N= 7690,30

N=7430,35


-0,24-0,26

-0,13-0,23

-0,07-0,20


0,290,54**0,90***

0,370,50*0,76***

0,360,57*0,89***


0,350,09

0,250,02

0,350,00-0,63

Subsidiary 0,62*** 0,68*** 0,73***Importance as source of informationUniversitiesTechnical/scientific institutes

0,110,52***

0,170,59***


-0,25***-0,17

36

Table 3-4 : Cooperative projects with private research institutions

Probit -Modelle I II III


N= 7940,18

N= 7350,23

N=7050,24


-0,55*-0,39*

-0,47-0,28

-0,19-0,23


0,501,24***0,97**

0,68*1,30***0,93**

0,88**1,57***1,25***


-0,130,04

-0,22-0,03

-0,11-0,100,14

Subsidiary 0,71*** 0,73*** 0,74***Importance as source of informationUniversitiesTechnical/scientific institutes

-0,090,40***

-0,130,30**0,27**


-0,14-0,28**

37

4 References

Arundel, A. und van der Paal, G. (1995), Innovation Strategies of Europe’s Largest IndustrialFirms. MERIT.

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