Assessing the Institutional Set-up of National Innovation Systems

Transcription

1 Assessing the Institutional Set-up of National Innovation Systems Henri Capron and Michele Cincera Université Libre de Bruxelles Unité d économie spatiale et de la technologie DULBEA-CP140 Avenue F.D. Roosevelt 50 B-1050 Brussels Track 1 Keywords: assessment, National Innovation Systems, institutions Abstract This paper aims at presenting a unified framework to assess National Innovation Systems (NISs) from an institutional perspective. Institutions play a central role in promoting and supporting the creative, absorptive and transfer capacities of NISs. Yet, the present literature does not report any operational guidelines regarding the assessment of institutional linkages underpinning such systems. There is therefore a need to develop an analytical framework empirically implementable to assess the institutional set-up of NISs. The analytical framework developed in the paper is based upon the following criteria: comparability of results across countries, representativeness of results on the institutional profile of countries, measurement issues of the institutional set-up and consistency of the approach with regard to the concept of institutions. As a basis for analysing the national institutional set-ups, the different angles at which institutional linkages can be observed are reviewed. This typology of linkages allows one to get a clearer view of the different aspects to take into account in any evaluation exercise as well as the main limits of such an enterprise. Once defined the complementary contexts, we focus on the implementation process of a knowledge-based policy with the view of identifying the different stages that underlie the government intervention. The main disseminators of institutional linkages reviewed are helpful to build an analytical framework for evaluation purposes that can help to deepen our comprehension of institutional linkages, to appreciate the strengths and weaknesses of institutional set-ups and to implement a benchmarking approach in the management of science and technology policy. 1. Introduction Although it is recognised that institutions play a central role in promoting and supporting of the creation, distribution and use of the knowledge-product in National Innovation Systems (NISs), the present literature does not report any operational guidelines with regard to the assessment of the institutional linkages underpinning NISs. As pointed out by Edquist and Johnson (1997), the concept of institution is not very clear, not much empirical knowledge exists on the influence of institutions on innovation and better conceptual tools than those we have at the moment are needed. On the political ground, they underline that case studies of the relations between institutions and organisations and their role for innovation would be an appropriate approach for the time being. In a same vein, Nelson (1993) emphasises the absence of a well-articulated and verified analytical framework linking institutional arrangements to technological and economic performance. He points out that the belief that the innovative prowess of national firms is determined to a considerable extent by government is challenged by the observation that case studies do provide scattered evidence on them, but, simply because they are so diverse that any strong generalisations that can be drawn. If it is obvious that institutions mater a lot in NIS, it is of great concern for countries to have a clear view of their institutional set-up. These few observations illustrate the usefulness to develop a coherent approach to assess the institutional set-up of NIS. The methodological caveat that it is suggested here is guided by the four following points: comparability of results across countries, representativeness of results with regard to the institutional profile of countries, measurement issues of the institutional set-up, consistency of the approach 1

2 with regard to the concept of institution. In the absence of any methodological guidelines in order to evaluate empirically national institutional set-ups at the international level, our main objective is hereafter to develop an analytical framework empirically implementable. In the second section, we describe a typology of linkages that allows one to have a clear view of the aspects to take into account in any evaluation of institutional set-ups. Once defined the complementary contexts, in which institutional linkages weave, we focus on the implementation process of a knowledge-based policy. The third section aims at identifying the different stages that underlie government interventions. The concepts reviewed in this section are helpful to build an analytical framework for evaluation purposes. The objective is to highlight the process that underlies policy interventions, which are expected to be the main disseminators of institutional linkages. The last section develops an evaluation method, which can help to deepen our comprehension of institutional linkages and to appreciate the strengths and weaknesses of institutional set-ups. The main question which guides this section, is: How can we concretely implement a suitable evaluation of institutions influencing the innovation systems? 2. Defining the institutional linkages It is clear that the assessment of the institutional mapping of NISs is directly (but not exclusively) linked to the role of government. Indeed, the institutional linkages are the main channels through which the technology policy is implemented. Metcalfe (1995) defines NISs as the set of distinct institutions which jointly and individually contribute to the development and diffusion of new technologies and which provides the framework within which governments form and implement policies to influence the innovation system. According to Nelson (1990), the job of institutional design is to get an appropriate balance of the private and public aspects of technology, enough private incentive to spur innovation, and enough publicness to facilitate wide use. A main task of the analysis is to elaborate a relevant typology of actors and of their interdependencies. Beside the formal relationships among actors, it is also of interest to have a view of the structural components, which influence the performance of NISs. A first look at the role played by governments can be obtained by distinguishing between the financing and performing entities as well as by identifying the categories of activity receiving the government support. Yet, this approach gives only some pieces of information on the role played by governments. Indeed, governments also influence the innovation process through indirect measures (public procurement...) and qualitative arrangements (legal framework...). Consequently, the understanding of the institutional learning and searching processes needs to overdo the data analysis of conventional indicators so as to get a clearer insight into the web of interactions between the main actors of NISs. We can identify five complementary and interrelated dimensions which are at the basis of any innovation system and whose scopes of action are summarised in Figure 1. All these dimensions are characterised by the presence of institutions influencing the design of national institutional systems as well as their relevance and effectiveness. At the top, we have the environmental context, which has very pervasive and diffuse effects on the innovation system. At the bottom, we find the organisational structure of S&T activities, which is the core of NISs and which is at the source of the specialisation of countries and of their global performance. Yet, this organisation is directly influenced by the policy design implemented by governments to enhance the development of knowledge. Consequently, it is worth analysing these complementary dimensions to have a clearer view of the institutional mapping of NISs. 1. The environmental institutional linkages deal with the rationale of government action in the social, economic and technological development. As put forward by Nelson (1993), the package of fiscal, monetary and trade policies differentiates countries in which firms are effectively innovative from those in which they are not. More globally, he points out the macroeconomic climate as a main feature affect- 2

3 ing the ability and the incentives of firms to innovate. The main types of interventions, which can have indirect but significant effects on the innovative activity are successively: labour policy, industrial policy, economic policy; trade policy; fiscal policy; monetary policy; infrastructure policy and regulatory framework. 2. The spatial institutional linkages draw the deep structure of NISs and are at the root of their coherence. According to Lundvall (1992), globalisation and regionalisation might be interpreted as processes, which weaken the coherence and importance of NISs. More specifically, the OECD (1992) underlines that regionalisation has become the cornerstone of national R&D and innovation policy. So, the apparent coherence of a NIS might hide important mismatches at the regional level. The other spatial component deals with the increasing of international S&T collaborations. The present techno-globalisation process challenges national governments, which face with increasing difficulties in the design of their S&T policy. More than ever, they are dependent on choices and decisions taken at a supra-national level. Consequently, governments are now challenged from below by regional and even sub-regional authorities and from above by supra-national entities. This leads to identify four decision levels in the implementation of S&T policy: local, regional, national and international. 3. The instrumental institutional linkages refer to the policy toolbox, which is at the disposal of governments to guide and stimulate innovative activities. It is composed with the policy-mix implemented by governments to foster the pursuit of technological achievement as a mean to improve welfare. The fine-tuning of the technology policy-mix, and consequently the set of instruments used, depends on the priority order attached by governments to their multiple objectives. As shown by Ergas (1989), government preferences effectively differ among countries according to the features of national institutional and economic environments. In order to appreciate to what extent countries make use of some instruments in preference to others, the taxonomy retained here is the following: supply policy; diffusion policy; S&T infrastructure policy; human resources policy. 4. The organisational institutional linkages are at the heart of the institutional mapping. If the institutional actors and their contribution to NISs is well known, it is less obvious to break the black box of their formal and informal interconnections so as to give evidence of mismatches, which restrain the efficiency of institutional linkages. Indeed, within each institution, there are diversified structures funded by a multiplicity of sources and consisting of many subsystems (Krull and Meyer-Kramer, 1996). It is the case of universities, which cover the full spectrum of research activities, co-operate with other organisations and are more and more engaged in regional development. An appropriate way to look at institutions that play a central role in NISs is to distribute them according to their functions in NISs: business organisations, higher education institutions, research and technology development institutions, bridging institutions and government policy institutions. 5. The sectoral institutional linkages at the level of economic activities as well as at the level of technological profiles define the techno-economic structure and competitiveness of countries. The question is here to investigate to what extent the institutional structure of S&T has an influence on national technological patterns. For instance, Johnson (1992) emphasises that a serious analysis of the institutional variety is a precondition for a better understanding of the significant differences in economic performance within industrialised economies. 3. The process of a knowledge-based policy Technological development is not pursued for its own sake but with the goal to improve global welfare. At first sight, this questioning could appear as trivial given the abundant theoretical literature on the rationale of public action in the field. Yet, the empirical observation of government attitudes leads to be sceptical about their comprehension of the major role played by S&T in the socio-economic develop- 3

4 ment. In the present period of budgetary austerity for many governments, education and training as well as public support to R&D are facing high budget reductions. Furthermore, it must be kept in mind that public intervention in S&T will not be automatically welfare improving. Besides the well-known market failures, the government actions to correct them can in fact be ineffective due to non-market failures (Wolf, 1979) and can even induce perverse effects. Given policy-institutions cannot be presumed to be sheltered from political and administrative rigidities, it is of great concern to assess how effective they are in co-ordinating, developing and stimulating the national innovation potential. The philosophy underlying the analytical framework developed here is based upon the scheme of interactions described in Figure 1. The nested boxes of this diagram highlight the complexity of the policy process. Each policy, even if it is not directly oriented towards S&T development, can have strong implications on the innovative activities of economic agents. In order to limit the scope of the assessment scheme, only the components directly linked to S&T policy are taken into account. The approach adopted refers to the scheme generally in use for the evaluation of public action in the field of economic policy. The assessment sketch so defined is drawn in Figure 2. As a whole, the goal of government action in public life is to upgrade social welfare. The achievement of welfare refers to the satisfaction of generic needs defined as constituting the quality of live. So, information, health, security, mobility... are all generic needs that can be only satisfied at a moment of the time by exploiting the technical knowledge available. These specific technological answers lead to the production of derived needs. The computer, health and transport industries... are channels through which these derived needs are satisfied. In order to optimise wealth creation due to the insatiability of generic needs and to limited resources, governments define objectives to be achieved and implement a set of policies appropriate to fulfil them. The development of S&T is one of the means allowing the society to improve its social welfare. Yet, it is now recognised that the broader concept of knowledge is more appropriate to understand the innovation process. It is the efficiency and the effectiveness in producing, diffusing and exploiting useful knowledge, which allows improving the well being. With reference to that, generating, acquiring and diffusing knowledge can be identified as the main objectives of government action. The creative, transfer and absorptive capacities have been viewed as the main characteristics which allow to appreciate the efficiency in the production and exploitation of technology flows at the source of knowledge accumulation. In a similar vein, the OECD (1997) operates a distinction between the knowledge production, the knowledge transmission and the knowledge transfer. According to David and Foray (1995), the knowledge distribution is becoming a critical attribute of innovation systems as important as the capabilities for generating new knowledge. These technology flows are themselves influenced by the characteristics of knowledge, which define the knowledge regime: its degrees of codification and disclosure as well as its ownership status. These characteristics define the knowledge-product space within which knowledge institutions evolve (David and Foray, 1995). Yet, they are not invariable but depend on the social organisation and the incentive structure of existing institutions. Consequently, the institutional mapping as represented by norms, rules, regulations and co-operation arrangements govern to a large extent the functioning of NISs. In a nutshell, these characteristics depend on institutional adjustments. The process according to which the objectives can be achieved will be determined by the policy mix implemented. The observation of market failures preventing a Pareto optimal allocation of resources gives the economic foundation of technology policy. The market mechanisms are not enough to solve the problem of asymmetric information and uncertainty at the heart of the innovation process, of externalities linked to the inability to appropriate fully the results of research activities as well as market imperfections which restraint the innovation propensity. Yet, the market failure approach does not provide a sufficient foundation for implementing strategic technology policy (Justman and Teubal, 1995). It is the compara- 4

5 tive effectiveness between government intervention and market mechanisms, which must guide policy choices. This implementation have to be based upon a diagnosis of the socio-economic situation and the technological position of the country in order to define on which components of the innovation system will be put the policy stress. On the basis of these elements, private as well as public policy-makers identify targets, which define the technology orientations, and priorities through which technology flows will mainly operate and new knowledge will be stimulated. The targeting of public intervention leads them to implement instruments which are mainly concretised through the institutional device in order to improve the effectiveness of these mechanisms. Yet, all the instruments are not systematically under the control of public authorities so that the effectiveness of public actions can be expected to be influenced by the degree of control of instruments by governments. So, it is useful to distinguish between control instruments which are under the command of governments (e.g., education budget) and influencing instruments which depend on the relative attractiveness of government actions for the targeted economic agents (e.g., enterprises reactions to R&D incentives). Although governments can make use of the full package of instruments, they will in fact select the instruments and will mix them according to the targeted policy. The institutional set-up is at the core of the instrumentation of the national knowledge-based system. Institutions are in charge of interventions making instruments operational. In fact, there is a myriad of institutions, which are expected to ensure the efficiency of NISs. They are not independent and vertical devices but are intertwined by a game of hierarchical and/or causal relationships (policy decision-makers, S&T administrations, universities, ) and interdependencies (university-industry collaborations...). As underlined by Metcalfe (1995), it is the mix of institutions, which are involved, and their interactions, which shape the whole process of technical change. So, an important task is to conceive the institutional matrix, which underlies the innovation system. These choices will lead to concrete quantitative and qualitative interventions, which will form the institutional set-up. The implementation of the policy-making mix so obtained leads to the technology performance that can be estimated and allow to evaluate the effectiveness of the institutional environment of NISs. The S&T specialisation and base will give evidence of the improvement brought to the S&T potential. Yet, as technological development is not the end but a mean what matters is the impact of S&T policy on the socio-economic performance. The effectiveness of the S&T policy can be measured by the improvements observed in the economic effectiveness, the social equity and environmental sustainability. The performance observed leads decision-makers to adjust their policy, i.e. the instruments, in order to take into account the new socio-economic environment and improve the effectiveness of the S&T policy. These adjustments can be viewed as the fine-tuning of the S&T policy. As part of the systemic appreciation of NISs, the institutional linkages deal with the diversity, the role and the use of existing instruments as well as the interactions between the different categories of instruments leading to the institutional mapping. In fact, we face a complex problem because there are strong interdependencies within each of the components defining the policy process. A main question of S&T policy is to realise the fine-tuning between the instruments available: How to allocate R&D resources among the different types of research? What is the most appropriate policy-mix to promote an efficient distribution of knowledge? Concretely, the proposition is to cross objectives, instruments and institutions on a quantified basis in order to structure information and ensure comparability. Consequently, in order to assess the efficiency of the institutional mapping, we must establish a preliminary taxonomy of objectives, instruments and institutions. On the basis of this taxonomy, we can implement several functional matrices linking each step of the policy process: 5

6 - the objectives - instruments matrix which describes the links between the objectives pursued through the S&T policy and the instruments used in order to achieve these objectives, - the institutions - instruments matrix which establishes the links between the instruments and the institutions in charge of their implementation, - the institutional interactions matrix which is an attempt at identifying the interconnections between institutions playing a predominant role in the innovation system. A first attempt to build such matrices is given in Tables 1 to 3. In order to clarify how to carry out the policy diagnosis on the institutional mapping, there is a need to review the main categories of indicators, their relevance and limits and to select the most appropriate ones to be included in each cell of matrices. Traditionally, S&T indicators are distributed into three large categories: inputs, throughputs and outputs. More recently, the stress has been put on the distinction between knowledge stocks and knowledge flows. In the list of indicators available, what should guide the choice is their capabilities to be connected with one of the four following categories: - the indicators of means: they deal with the financial and human resources allocated to an institution as well as the organisational and regulating modalities of interventions. - the indicators of realisations: we are here concerned with physical outputs and intangible services supply from institutions as the number of files managed and the number of contacts... - the indicators of results: they are representative of the direct reactions of recipients to the activities of institutions and concern the amount of subsidies, loans, tax credits, the number of co-operation s, the number of patents and licenses, co-patents... - the indicators of impacts: they measure the indirect, induced and delayed effects of interventions as the rent and technology spillovers, the effect of public subsidies on private R&D, productivity,... The first two ones give some relevant pieces of information about the internal management of institutions. They are under the full control of decision-makers. The last two ones are based upon the direct and indirect interactions between the institutions and the recipients of interventions. Depending on the reactions of the recipients of services supplied by institutions, they are not under the control of institutions. The combination of these indicators allows one to appreciate the efficiency of institutions. The effectiveness indicators will help to diagnose how well the institutions perform their function. They can be obtained by comparing the indicators of means and realisations to the indicators of results and impacts. As a main objective of the approach is to collect indicators in order to fill in the cells of institutional matrices, the empirical content so obtained will serve also as a basis to appreciate the functions that are under-performed in NISs. The building of comparable institutional matrices for countries should also make possible to develop benchmark indicators. A proposal is to select the highest efficiency indicators among countries in order to evaluate the efficiency gaps of institutions for each country. The differences between the benchmark indicators and the country efficiency ones could be interpreted as measures of the degree of functional mismatch of the institutional set-up. A review of national statistics shows that further efforts should be devoted to the collect of new categories of indicators about the means, the realisations and the results relative to the functioning of institutions. Despite the difficulty of the task, a high value-added can be expected from such an exercise. 4. Conclusion In order to develop a coherent approach that ensure the comparability of results among countries, we must have a taxonomy of objectives, instruments and institutions composing NISs. There is also a need to find a good trade-off between the degree of deepening of the diagnosis of the institutional mapping and the information to be collected. If we can consider that institutions are to a large extent represented 6

7 in a major part of countries, their denominations and functions can substantially differ, what makes important to have a clear definition and taxonomy of institutions. Yet, institutions are not mono-objective but multi-objective, what makes difficult to put them in specific categories. Furthermore, if institutions have copycat behaviours with regard to successful measures developed elsewhere their also try to adapt the strategy to their socio-economic environment and to bring some additional value-added to the actions. There are also large organisational differences in the management of S&T policy among countries due to the political system and historical reasons. Finally, what is important in NISs, is to analyse the role played by strategic nodes. Yet, the large divergences among orientations and priorities selected by countries imply that these nodes also differ across countries. The high diversity of cultural patterns, industrial specificity and technological specialisation also explain why apparently similar institutions can work differently across countries. The high diversity of institutional set-ups reinforces the need to identify the generic functions of institutions to compare national institutional set-ups. The taxonomies of objectives and instruments included in Tables 1 and 2 represent an attempt to classify these functions on the basis of the methodological guidelines discussed in the paper. References David P. and Foray D. (1995), Assessing and Expanding the Science and Technology Knowledge Base, STI Review, n 14, pp Edquist C. and Johnson B. (1997), Institutions and Organizations in Systems of Innovation, in Edquist C. (ed.) Systems of Innovation: Technologies, Institutions and Organizations, Pinter, London, pp Ergas H. (1989), Global Technology and National Politics, Council of Foreign Relations, New-York. Justman M. and Teubal M. (1995), Technological infrastructure policy (TIP): creating capabilities and building markets, Research Policy, 24(2), pp Johnson B. (1992), Institutional Learning in Lundvall B.-A. (Ed), National Systems of Innovation, Towards a Theory of Innovation and Interactive Learning, Pinter Publishers, London, pp Krull W. and Meyer-Kramer F., Science, Technology, and Innovation in Germany - Changes and Challenges in 1990s, in Krull W. and Meyer-Kramer (eds), Science and technology in Germany, Cartermill, London, 1996, pp Lundvall B.-A. (1992), National Systems of Innovation, Towards a Theory of Innovation and Interactive Learning, Pinter Publishers, London. Metcalfe S. (1995), The Economic Foundations of Technology Policy: Equilibrium and Evolutionary Perspectives, in Stoneman P. (ed.), Handbook of the Econimics of Innovation and Technological Change, Blackwell, Oxford, pp Nelson R. (1990), Institutions Supporting Technical Change in the United States, in Dosi G. et al. (eds.), Technical Change and Economic Theory, Pinter Publishers, London, pp Nelson R. (1993), National Innovation Systems, A Comparative Analysis, Oxford University Press, Oxford). OECD (1992), Science and Technology Policy, Review and Outlook 1991, Paris. OECD (1997), Science and Technology Policy, Review and Outlook 1996, Paris Wolf C. (1979), A Theory of Nonmarket Failure: Framework for Implementing Analysis, Journal of Law & Economics, 22(1), pp Bio-Sketch Henri Capron has a Business and Management degree, a MBA in Econometrics and a PhD in Economics and is professor of economics at the University of Brussels. His current work focuses on regional development strategies and the economics of innovation. Michele Cincera has a MBA in Econometrics and a Ph.D. in Economics. He is a lecturer at Université Libre de Bruxelles and a consultant at the Belgian Federal Office for Scientific, Technical and Cultural Affairs. His research interests embrace the assessment of innovative activities as well as their outcomes. 7

8 International environmental context National environmental context Local & regional environmental context Instrumental choices S&T policy. Supra-national institutions. Economic environment & international agreements. Parliament, ministeries & advisory committees. Economic, industrial, fiscal, monetary, trade policies. Labor policy & regulation. Parliament/Council, ministeries/secretariats, advisory committees. Regional development agencies & strategies Administrative bodies: Policy focus: Supply programmes, diffusion programmes, S&T infrastructure programmes Competitiveness, integration, convergence, public goods Organisational structure.regional agencies. National agencies. Supra-national organisations Local & regional initiatives National S&T policy support International interweavements. S&T support. Science base support. Community support. R&D incentives. R&D incentives. International research institutes. Regional technology plans. International collaborations. Megascience alliances. International S&T cooperations Sectoral interactions Knowledge generation, acquisition & use Knowledge transmission Knowledge orientation. Academic training & priorities. Vocational training. Generic technologies. Apprenticeship training. Technology for public goods. Learning. Environmental concerns Bridging institutions RTO's Knowledge regime. S&T centres. Government labs. Degree of accessibility. University interfaces. Joint RC's. Degree of disclosure. Business centres Clusters. Research institutes. Degree of codification Networks Specialisation Knowledge financing Linkages. Public financing Business organisations HERC's. Financial institutions. Firms. University RC's. Risk capital funds. Private research centres. Inter-university RC's. External sources. Consultancy agencies. Research communities NIS effectiveness Knowledge capabilities Knowledge performance Global performance. Firm innovation capability. RTA's. Economic growth. University research capability. RSA's. Social equity. S&T networks. Technology base. Environmental sustainability. Institutional interactions. Science base. Education programmes Education &. Training programmes training policy Figure 1. Framework of the national innovation system 8

9 GOALS Welfare: Improving living standards - Efficiency - Equity - Sustainability OBJECTIVES REGIMES Increasing the distribution power - degree of formalisation - Creative capacity - degree of disclosure - transfer capacity - ownership status - absorptive capacity INSTITUTIONALISATION Policy-making institutions SOCIO-ECONOMIC TARGETS ENVIRONMENT - S&T priorities - opportunity windows - S&T orientations - emerging technologies - competition INSTRUMENTS - supply policies MARKET FAILURES - diffusion policies - asymmetric information - S&T infrastructure policies - externalities - human resources policies - market imperfections - competition, economic & economic policies INTERVENTIONS Knowledge- transmitting Financing institutions institutions - education institutions - venture capital institutions - training institutions - policy-implementing institutions S&T inplementing institutions - Business organisations - RTO's - HERC's - Bridging institutions TECHNOLOGICAL PERFORMANCE - RTA's - RSA's - technology base - science base SOCIO-ECONOMIC PERFORMANCE - economic growth - social equity - environmental sustainability Figure 2. The S&T policy evaluation 9

10 Table 1. Objectives and instruments Family of instruments Supply policies Diffusion policies Infrastructure policies Human resource policies Main objectives A. Creative capacity -fundamental research -applied research -pre-competitive research -near-market research -experimental development -megascience -infratechnology -technology for public goods -design B. Transfer capacity -producer-user knowledge exchange -knowledge diffusion -knowledge adoption C. Absorptive capacity -receptivity to knowledge -accessibility to knowledge -acquisition of knowledge -distribution of knowledge -updating knowledge -implementation of knowledge Global weight of instruments R&D support R&D promotion R&D incentives risk capital, seed money technology transfers patenting & licensing government procurement technical standards S&T parks technology centres S&T cooperatio documentation centres incubators & business centres education vocational training apprenticeship agreements Competition, economic & labour policies investment incentives market information export promotion labour mobility Global weight of objectives 10

11 Table 2. Institutions and instruments Family of instruments Supply policies Diffusion policies Infrastructure policies Human resource Institutions A. Business organisations -business enterprises -private research centres -industry & professional associations -consultancy firms B. Government policy institutions -parliament & ministries -advisory bodies -regulatory agencies -support & promotion organisations -co-ordination institutions -local & regional authorities -supra-national institutions C. HEIs -universities -other HEIs D. RTOs -(inter-)university research centres -international research communities -non-profit research organisations -other RTOs E. Bridging institutions -university interfaces -vocational training institutes -science parks -incubators & business centres -documentation centres F. Venture capital organisations -commercial banks -risk capital, start-up & seed money funding organisations R&D support R&D promotion R&D incentives risk capital, seed money technology transfers S&T cooperation patenting & licensing government procurement technical standards S&T amenities overhead services supply technological interweavements information amenities policies education vocational training apprenticeship agreements Competition, economic & labour policies investment incentives market information export promotion labour mobility Global weight of institutions 11

12 Table 3. Institutional interactions INSTITUTIONS A. Business organisations A. Business organisations -business enterprises -private research centres -industry & professional associations -consultancy firms B. Government policy institutions -parliament & ministries -advisory bodies -regulatory agencies -support & promotion organisations -co-ordination institutions -local & regional authorities -supra-national institutions C. HEIs -universities -other HEIs D. RTOs -(inter-)university research centres -international research communities -non-profit research organisations -other RTOs E. Bridging institutions -university interfaces -vocational training institutes -science parks -incubators & business centres -documentation centres F. Financing organisations -commercial banks -risk capital, start-up & seed money funding organisations B. Government policy institutions C. HEIs D. RTOs E. Bridging institutions F. Financing organisations 12