The concept of an innovation system

Defining and describing innovation systems is not an academic concern.

It has major implications for the balance and mix of policies needed to improve innovation system performance and for the amount of communica-tion and co-ordinacommunica-tion required to create holistic innovacommunica-tion policies. To the extent that countries operate with a narrow “innovation system map” focused on science and technology and the formal R&D system, they are likely to be guided into making policy choices that optimise the formal part of the system at the expense of the whole. During the current decade, a broader perspective on innovation systems is underpinning attempts by governments to develop holistic innovation and research policies, as has certainly been attempted in the Nordic countries (Arnold et al., 2006) and strongly advocated in the UK (NESTA, 2006).

Achieving an appropriate balance among systems components and policies requires adequate resources and governance, mixing co-ordination and strategy with the flexibility and receptiveness to bottom-up initiatives necessary to adjust to changing realities. Policy makers and other stakeholders need continuous information about the innovation system; they also need to develop open systems able to reflect on performance (for example through evaluation) and to consider future opportunities. Hence, there is a need for information – strategic intelligence – about the system as a basis for making policy. Some of this comes through the normal activities of actors such as innovation agencies, which collect information and

experience as they work. Other intelligence comes from dedicated studies and special exercises such as foresight and planning. Evaluation provides a significant feedback loop. These elements taken together provide the information basis for policy learning, while the ability of the system and its component actors to make use of the information and to adapt and improve policies over time depends not only on the availability of information but, crucially, on having institutions and governance arrangements in place that can effectively connect knowledge to policy practice.

The innovation systems concept is allied to a number of important ideas – specifically about how innovation functions and who is involved – which are essential to an understanding of such systems.

Box 1.6. The evolution of the national innovation systems concept

Christopher Freeman introduced the term “innovation system” into the literature in a study that aimed to explain and learn from the success of Japanese research and innovation policy (Freeman, 1987). At that point, Freeman’s definition was rather narrow: he referred to the state institutions involved in defining and performing research and innovation policy.

Subsequent work collected in Nelson (1988, 1993) and Lundvall (1988, 1992) widened the definition of national innovation systems considerably to include industry and more of the national context within which research and innovation took place. Lundvall’s perspective (inspired by the highly networked SME structure of Danish industry) focused on the interactions between business enterprises as users and producers of innovative technologies.

Business enterprises were therefore put at the centre of the innovation system, although the importance of wider cultural and macro-system environments was also highlighted.

Subsequent studies (e.g. Metcalfe, 1995; OECD, 1999; OECD, 2002), define a national system of innovation as a set of distinct organisations (e.g. firms, research institutes, universities) which jointly and individually contribute to the development and diffusion of new technologies. They do so within a wider set of institutions and social, economic and political conditions that influence the organisational actors and provide the framework within which governments form and implement policies to influence the innovation process. It is, therefore, a system of interconnected organisations or core actors and wider framework conditions within which societies create, store and transfer the knowledge, skills and artefacts which contribute to innovation. From this perspective, the innovative performance of an economy depends not only on how individual organisations perform in isolation, but also on how they interact with each other and their interplay with social institutions such as values, norms and legal frameworks (Smith, 1996). In effect, each component of the system needs to work at least at an acceptable level of quality and efficiency and the linkages between them need to function well.

Interconnection and interdependence are at the heart of the innovation system concept. The innovation systems perspective originated in deliberate opposition to simpler, more or less monocausal views of innovation and the economy. Modern models of the innovation process are complex, with many linkages among actors (Mowery and Rosenberg, 1978; Kline and Rosen-berg, 1986). Innovation processes do not always start at one particular place (basic science or the market) but can be prompted by changes anywhere.

Innovative activity encompasses a wide range of phenomena. Innovation systems are not concerned solely with the types of innovation that are globally novel. A lot of the strength of the Norwegian innovation system comes from its effective use of technologies developed elsewhere. It is now recognised that important forms of innovative activity include changes that are new to particular industries or individual firms. Innovation also encompasses not only “hard” technological innovations, but also softer forms concerned with organisational arrangements and procedures. Norway, for example, is strong in some of these areas, especially those that are enabled by harmonious labour relations in an economy with high employ-ment, skills and easy labour mobility.

Innovation activities are much more than R&D. Discussions about the core scientific and technological functions in national innovation systems often jump quickly from “science and technology” to “research and develop-ment”. Consequently, maps of the R&D system easily become taken as maps of the innovation system. This tends to be reinforced by heavy reliance on data on R&D inputs and outputs as indicators of the main features of innovation systems. This seriously distorts the picture because it leaves out many other kinds of S&T activity that play important, central roles in innovation.

Design, engineering and management play key roles in innovation systems. The core activity at the heart of almost all innovation is the creation of a set of specifications (or designs) of the change that is to be brought into use. These may consist of complex computer-aided designs, or specifica-tions for procedures and organisational arrangements. In complex, one-off projects such as designing and building equipment to exploit the more difficult North Sea oil and gas fields, these skills are indispensable, and the degree of novelty involved in individual projects can mean that they are hard to distinguish from R&D skills. Indeed, in many cases, such a distinction may be, in practical terms, meaningless.

However, R&D activities may nevertheless play an important role even in this type of innovation. On the one hand, design, engineering and management may be carried out on the basis of recently developed new knowledge, perhaps even created by R&D activity from another source. In

these cases they contribute to the process of translating knowledge outputs from R&D into the concrete realities of implemented innovation. Second, in addition to the “supply side” role, design, engineering and management activities play an equally important role in the other direction – from the production of goods and services to the execution of R&D. When innovators’ existing knowledge base is inadequate to meet the demand for innovation, they actively “pull” on R&D to supply new knowledge. ²⁸ Moreover, this pull on research or technological development is not simply a vague demand for innovation in general. Instead, these activities serve to concretise generalised demand into specific technical configurations or performance requirements that help to shape the process of technological development.

Business enterprises are central actors in the system. Since the earliest contributions to ideas about the innovation system, different emphases have been placed on different system components (see Box 1.6). Numerous reports have focused on public sector organisations and policy-making structures, leaving business enterprises as minor entities on the edge of system maps. In some cases, national innovation systems have been defined almost exclusively in terms of public-sector actors, quite commonly depicted within hierarchical structures through which they influence and drive other actors, including business enterprises. Other studies put business enterprises at the centre of the innovation system, and public scientific and technological organisations are somewhat peripheral. This report is based on a combination of these two perspectives. Finding the right balance between policies addressing the business sector and the knowledge infrastructure is a key task for policy makers.

Demand, not just supply, drives innovation systems. It is now common to argue that linear models of knowledge running in one direction from R&D to commercialisation provide an inadequately simplified representation of what happens in the innovation process. This model has thus been extended to include various knowledge flows running in the opposite direction (from markets to research) as these are highlighted as drivers and shapers of the innovation process. The articulation of effective demand for innovation and for knowledge and skill inputs to innovation is centrally important in stimulating or constraining innovation and the directions it takes. Policy implications include the opportunity to use

28. Indeed, R&D is often not a source of innovation but an effect of innovation decisions (Smith and West, 2005). From this perspective R&D should be seen not only as a process of discovery but also as a problem-solving activity within existing innovation processes.

procurement and regulation as well as improved supplier-user communica-tion and partnership as ways to encourage innovacommunica-tion.

Innovation functions do not map tidily to organisations. Many approaches define innovation systems primarily in terms of organisations (universities, research institutes, firms, etc.). It is important to highlight that single functions rarely map to single types of organisation. Many of the key organisations in innovation systems are multifunctional; for example, universities have extended their traditional function of basic/strategic research to technology development and even further downstream to design, engineering and entrepreneurship. The functions of universities and applied research institutes increasingly overlap at the more fundamental end of the range of such institutes’ activities (Arnoldet al., 2007). Similar functions may be undertaken in different organisations; for example, part of the process of creating scientific and technological human capital for innovation systems is carried out by specialised education and training organisations, but a very important part is also carried out by business enterprises via large expenditures on education and training and by active management of the process of experience accumulation. Mappings between functions and institutions that work in one innovation system may not be transportable to others. For example, under other circumstances, companies might do some of the applied work done by industrial institutes in the Norwegian system.

National systems are internationally open. International components of the system are increasingly diverse. For example:

x Inward flows of technology embodied in final consumer goods and services.

x Collaboration along international value chains in creating, transferring and implementing innovation in local production for export.

x The execution of local investment projects that draw on imported engineering and project management services, licensed technology and capital goods.

x Collaboration with foreign partners in scientific research or techno-logical development.

x Inward and outward flows of FDI by multinational enterprises.

x The emigration, return and original immigration of all sorts of qualified scientific and technological human resources.

x Inward and outward flows of students.

The quantities, qualities and directions of all these flows are highly variable, and that variability has major implications for the domestic parts of the national innovation system. In many countries the active management of these international interfaces of the innovation system is increasingly seen as a major area for policy attention.

1.4.2. The government can help improve innovation system