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Holistic Innovation PolicyTheoretical Foundations, Policy Problems, and Instrument Choices$

Susana Borrás and Charles Edquist

Print publication date: 2019

Print ISBN-13: 9780198809807

Published to Oxford Scholarship Online: May 2019

DOI: 10.1093/oso/9780198809807.001.0001

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Innovations

Innovations

A Systems Activities Approach

Chapter:
(p.15) 2 Innovations
Source:
Holistic Innovation Policy
Author(s):

Susana Borrás

Charles Edquist

Publisher:
Oxford University Press
DOI:10.1093/oso/9780198809807.003.0002

Abstract and Keywords

This chapter comes to grips with the nature of innovation and systems of innovation. It identifies ten specific activities that define systems of innovation. The ten activities are specific elements directly related to the performance of innovation, that collectively shape the way in which innovation takes place in an innovation system. We call this a ‘systems activities approach’, and it is a broad version of the systems of innovation approach. These activities are partly performed by private organizations and partly by public organizations. The theoretical basis for innovation policy proposed in this book is built from the identification of the concrete problems (failures, bottlenecks, weaknesses, etc.) that afflict innovations and their determinants in systems of innovation, including those problems that might be the unintended consequences of policy itself.

Keywords:   innovation policy, systems of innovation, grand challenges, policy instruments, innovation processes, holistic, procurement, mission-oriented, R&D policy, additionality

2.1 Introduction

‘Innovation’ and ‘system of innovation’ (SI) are notions that have gained substantial currency over the past few decades. Seen as a crucial dimension of economic growth and prosperity, as a source for improving social development, public health, environmental protection, etc., social scientists and policy-makers have tried to understand and decipher in which way and how to foster innovation. This includes influencing the rate (speed) and direction of innovation processes.

Analysts, policy-makers, and politicians have also tried to reflect critically about the boundaries of innovation, its trade-offs, and possible ethical dilemmas. However, no matter how fascinating these endeavours are, there continues to be a lack of conceptual clarity regarding what exactly innovation is, what exactly SIs are about, and what governments can do about problems afflicting them. Much of the lack of clarity these days has to do with the rapid blurring of the meaning of ‘innovation’. This is due to a certain ‘inflation’ in its academic and conventional use, as well as within the rapidly changing context of innovation processes.

This chapter looks into these key conceptual and contextual matters as a way of setting up the foundations of the rest of the book. In particular, it focuses on two interrelated items. Firstly, the issue of ‘what innovation and innovation systems are’, which is not a trivial matter. The widespread use of the concept of ‘innovation’, in many different areas with many different meanings, requires clarification. We will delve into considerations about concept-stretching. Thereafter, we will formulate explicitly our own definitions of ‘innovation’, ‘system of innovation’, and other key concepts that will be used in this book. We clarify terms and notions, making clear what (p.16) we include in these concepts and what we do not include, i.e. where the boundaries are. The presentation and discussion of these definitions will be embedded in theory, i.e. the relations between some of the concepts are also addressed.

Secondly, this chapter focuses on what ‘happens’ in SIs, which means that we address the ‘activities’ in SIs. This is our way of explaining what we mean by the systems activities approach. In so doing, we address the ‘activities’ in SIs by identifying ten activities that influence innovation processes. This chapter is devoted to unfolding, one by one, each of these ten activities, specifying the key activities in a dynamic perspective. The identification and definition of these ten activities is an essential stepping stone for Chapter 3.

It is important to note that our conceptual specifications do not exclude the possibility of alternative definitions of these concepts. Stipulative definitions are not right or wrong; they are good or bad for certain purposes. We choose the definitions and conceptual specifications below simply because they serve our purposes and we consider them to be reasonably clear. There are myriad other possible ones and it is futile to argue about them. Hence, we present our concepts briefly, without arguing in detail for our choices or explicitly comparing with the choices of others. We hope that our specification of the basic concepts provides a clear and solid basis for the analysis in the rest of this book. Hence, we present definitions that suit the purposes of our analysis, briefly and sharply. The concepts we chose, of course, stem from the history of the analyses of innovation processes, innovation systems, and the analysis and design of innovation policy.

2.2 What Is an Innovation?

Innovations are defined here as new creations of economic or societal importance, usually performed by firms. However, firms do not normally innovate in isolation, but in collaboration and interdependence with other organizations (actors or players), which are parts of SIs. These organizations may be other firms (suppliers, customers, even competitors) or non-firm entities such as universities and financing organizations. Innovations may be brand new, but are more often new combinations of existing elements, i.e. existing knowledge elements can be integrated into an innovation. Hence, innovations certainly do not need to be based on new scientific breakthroughs.

Innovations can be new or improved products or processes. New—or better—products (product innovations) may be material goods or intangible services; it is a question of what is produced. New—or better—processes (p.17) (process innovations) may be technological or organizational;1 here, it is a question of how the products are produced. Innovations are certainly not only technological and material.

Process innovations have been product innovations in earlier incarnations. This means that product innovations play a more dynamic role in the renewal of an innovation system and an economy than process innovations (Edquist et al., 2001a).2 In this taxonomy, only goods and technological process innovations are material; the other categories are non-material and intangible. Thus, for example, innovations in service products are considered to be non-material or intangible innovations. So too are organizational process innovations.

Of great importance, however, is that the new creations do not become innovations until they are actually commercialized or diffused (i.e. spread) to a considerable degree. The development of a prototype or a test series are not enough for research results to qualify as innovations. New creations that are not commercialized or diffused in other ways are not innovations at all (OECD, 2005).3

The innovation concept used in this book is wide and includes product innovations as well as process innovations. It also includes the creation as well as the diffusion of new products and new processes to additional firms (possibly in other countries).4 And it includes innovations in all sectors of society, the public as well as the private sector.

(p.18) However, in recent years, there has been an ‘inflation’ in the use of the innovation concept. Innovation has become a buzz word on the lips of scholars from various disciplines, policy-makers, consultants, etc. This tremendous attention has produced a large variation of understandings and meanings of innovation. There is currently a great number of notions like ‘open innovation’ (Chesbrough, 2003; OECD, 2008), ‘service-sector innovation’ (Miles, 2005; Rubalcaba, 2006), ‘innovation in the public sector’ (Bartlett and Dibben, 2002; Hartley, 2005), ‘frugal innovation’ (Zeschky et al., 2011; Prahalad, 2012), ‘employee-driven innovation’ (Høyrup, 2010), etc.

We do not undertake a literature review of the many recently proposed widenings of what innovation can be because it is beyond the scope of this book. As an example, we will just mention ‘social innovation’, a concept that has become increasingly popular (Domanski et al., 2014; Nicholls et al., 2015; Maclean et al., 2013). When used, the concept of ‘social innovation’ often means making innovations with the objective of solving social problems or meeting social challenges. ‘Social innovation’ refers to highly respectable and very important issues. However, we believe that it is not useful to regard them as a certain class of innovation, just as we do not want to consider scientific progress (like Albert Einstein’s general theory of relativity), institutional change (like changes in constitutional law), or new cultural achievements (a new film) to be innovations. We prefer to see some of these ‘open innovations’, ‘social innovations’, employee-driven innovations, etc. as ordinary product and process innovations (see definition above) that have consequences for solving social problems and for mitigating social challenges. Hence, social innovations are a matter of objectives and directionality (and consequences) of pursuing innovation processes and innovation policies.

In this book, only product and process innovations as specified above are therefore considered to be innovations. This means that new markets, new research results, new patents, new organizations, new institutions, etc. are not called ‘innovations’ here. We prefer to defend some limits to what is included in the category of innovation, and be clear about the boundaries of the concept. We strongly stress the crucial role of new markets, new research results, new institutions, new organizations, and new institutions in innovation systems—but we do not call them ‘innovations’. These phenomena are instead determinants of innovations and are here dealt with in terms of ‘activities’ in innovation systems that influence the development of (product and process) innovations. The main part of this chapter is devoted to an identification and discussion of these key activities.

The development of innovations can be regarded as investments that are subject to risk and uncertainty. Some people might believe that ‘more innovation is always better’. However, this is not the case. We cannot take for granted that more innovation is better. At the same time we cannot determine (p.19) how much innovation is ‘optimal’. This is certainly a dilemma that is not solvable and we have to live with it and deal with it. Neither can we argue that innovations are always good nor bad. They are not value neutral. There are, for example, innovations that destroy the environment and there are others that improve environmental conditions. It is in such contexts that innovation policy tries to influence the direction of innovation processes by pursuing certain objectives (Edquist, 2011; Section 3.6. of this book).

The definitions of the key terms introduced in this chapter and in Chapter 3 are summarized in Box 2.1. Some of them will be discussed in more detail in later sections of this chapter and in Chapter 3. This is particularly true for activities in innovation systems, and concepts related to innovation policy in Chapter 3 of this book.

2.3 What Is an Innovation System?

The processes through which innovations emerge are complex; they (often, but not always) have to do with the emergence and diffusion of new knowledge elements, as well as the ‘transformation’ of these into new products and new production processes. The behaviour of organizations (such as firms5) is also shaped by institutions—or rules of the game—that constitute incentives and obstacles for innovation. These organizations and institutions are components of systems for the creation and commercialization of innovations. Innovations emerge in such SIs. The constituents of SIs include the components (organizations and institutions) of the systems as well as the relations among those. The main role of SIs is to pursue innovation processes.

The so-called linear model dominated innovation studies and innovation policy in the early days (Bush, 1945). This linear model was based on the assumption that innovations are applied scientific knowledge. The model was called ‘linear’ because innovations were assumed to be generated by a process consisting of well-defined, consecutive stages, e.g. basic research, applied research, and development work, resulting in new products and processes that ultimately influence growth and employment as well as societal and environmental problems. It was a supply and technology-push view.

However, research does not automatically lead to innovations, and innovations need not be preceded by research. Scientific knowledge that may lead to (p.21) inventions is not sufficient; it has to be transformed into commercialized innovations in order to mitigate societal and environmental problems and create growth and employment. The goal should never be to enhance innovation as such or in the abstract. Innovations should always have a purpose. Innovations themselves, as such, are not interesting, but their consequences are.

Some research results are never transformed into innovations, and research is only one of the many determinants of the development and diffusion of innovations. Above all, research is never sufficient to achieve innovations, and it is certainly not always necessary. Most innovations are developed without a direct basis in new research.

The SI approach, which has diffused rapidly during the latest decades, has completely replaced the linear view in the field of innovation research. This approach is very different from the linear approach. It is usually, in its different versions, defined in terms of determinants of innovation processes, although different determinants are emphasized in different versions (Freeman, 1987; Lundvall, 1992; Nelson, 1993; Braczyk et al., 1998; Carlsson, 1997; Cooke, 2001a; Bergek et al., 2008). The SI approach is also used in policy contexts by regional organizations (Cooke et al., 1997), national governments, public agencies, and international organizations such as the Organisation for Economic Co-operation and Development (OECD), EU, the United Nations Conferences on Trade and Development, United Nations Industrial Development Organization, etc. We will address innovation policy and the SI approach in more detail in Chapter 3.

The pioneers in the development of the SI approach were the books of Lundvall, and of Nelson and Rosenberg.6 Both define national SIs (NSIs) in terms of determinants, or factors, affecting innovation processes, although they point out different determinants as important in their definitions (Chaminade and Edquist, 2006; Edquist, 2014d). Lundvall writes that the ‘structure of production’ and ‘the set of institutions’ together define an SI (Lundvall, 1992, p. 10). Nelson and Rosenberg emphasize the organizations that support R&D—that is, the organizations that support the creation and dissemination of knowledge—as the main source of innovation (Nelson and Rosenberg, 1993).

If all the factors that influence innovation processes cannot be included in the definition, we have to choose the potential factors that should be excluded, and motivate why. This is difficult, because at any given moment we do not know, systematically and in detail, what all of these determinants are. It seems risky to exclude certain potential determinants, as these may prove to be important when our knowledge has increased. Thirty-five years (p.22) ago, for example, it was natural to exclude interaction between organizations as a determinant of innovation processes. Today, we know that these are very important (Camagni, 1991; Edquist and Johnson, 1997; Edquist, 2005; Cunningham and Ramlogan, 2016; Haakonsson and Slepniov, 2018). Therefore, a broad definition, including all possible determinants, is highly preferable.

Interactive learning has been central to the concept of NSIs from the beginning (Lundvall, 1992). The main components of an innovation system are often said to be organizations and institutions. In our view these two categories should be clearly distinguished from each other, but they are often not. For us more useful stipulative definitions follow.

Organizations are formal structures (e.g. hierarchies) that are consciously created and have an explicit purpose. They are actors or ‘players’. Examples include companies, universities, and policy organizations.

For their part, institutions are laws, rules, regulations, routines, and habits. They are the ‘rules of the game’. Institutions may be external to organizations, or located inside them. Organizations may influence institutions and they may be influenced by them. Key institutions in innovation systems are patent laws, national laws, and rules that govern the relations between companies and universities, rules governing the approval of drugs, rules and laws governing public procurement, etc. (Edquist and Johnson, 1997).7

Most of the attention in innovation research has long been paid to the components (organizations and institutions) of SIs in a static way, e.g. by Lundvall, and Nelson and Rosenberg. Less has been said about the processes that occurs within the systems and how they change. We choose such a dynamic approach and we label it a ‘systems activities approach’.

As we have seen, traditional SI approaches, such as Lundvall (1992) and Nelson and Rosenberg (1993), focused strongly upon the components within the systems, i.e. organizations and institutions. Since the late 1990s, some authors have addressed issues related to the specification of activities influencing the main role of SIs (Galli and Teubal, 1997; Liu and White, 2001; Johnson et al., 2002). Such a focus on ‘activities’ (also sometimes called functions) within SIs emphasizes strongly what ‘happens’ in the systems—rather than their components. In this sense the systems activities approach pursued here provides a more dynamic perspective—an issue to which we will return in Section 2.4.8

(p.23) We chose the term ‘activities’ to denote the determinants that influence the development, and diffusion and use of, innovations. Examples are R&D (as a means for the development of economically relevant knowledge that can sometimes provide a basis for innovations—Chapter 4 of this book), or the financing of the commercialization of such knowledge, i.e. transformation into innovations (Chapter 10 of this book). An alternative term to ‘activities’ is ‘functions’ (Hekkert et al., 2007; Bergek et al., 2010). We chose the term ‘activities’ in order to avoid the connotation with ‘functionalism’, the traditional approach in classic sociology. Classical functionalist sociologists tended to focus on the consequences of a phenomenon rather than on the causes (determinants). Our focus is on the causes (determinants) of innovation (Edquist 2005: footnote 16), rather than its consequences. As mentioned above and below, other colleagues prefer the term ‘function’ to denote almost the same thing.

One way to address what occurs within SIs is as follows. On a general level, the main dynamics of the innovation system is to drive or enhance innovation processes, i.e. to develop and disseminate innovations. What we call the activities in innovation systems are those that affect the development and diffusion of innovations. Examples of such activities are R&D and financing, as mentioned above. As we will see in Section 2.5, there are many other activities.

There are many specifications and definitions of the SI approach. For us, innovation systems should be defined as ones that include ‘all important economic, social, political, organizational, institutional and other factors that influence the development, diffusion and use of innovations’, as well as the innovations themselves (Edquist, 1997, pp. 3, 11–12; 2005, pp. 184 and 190–1, 2011; Borrás and Edquist 2013a and 2013b).

Hence, innovations can be seen as the output, whereas the innovation system is also constituted by a set of activities or determinants that influence such output. This is a wide definition; much more comprehensive than earlier ones. At the same time, the innovation system should not be considered as being the same as the whole economy or the whole society. It is much more sensible to limit the notion of innovation system to be constituted by innovations of various kinds and all the activities or determinants that influence their development and diffusion. The activities that are performed in innovation systems will be detailed later in Section 2.4.

Innovation systems may be national, regional, or sectoral. These three perspectives may be clustered as variants of a single generic SI approach (Edquist and Johnson, 1997). Much of the discussion here is based on the premise that the different variants of SI coexist and complement each other (p.24) (Tödtling and Trippl, 2005) (Amable et al., 1997). Whether the most appropriate conception of the SI, in a certain context, should be national, sectoral, or regional depends, to a large extent, on the questions one wants to ask.

We believe that a systematic emphasis on activities or determinants within SIs will become crucial for the development of both innovation theory and innovation policies in the future. It is also by influencing the determinants of innovation that enterprises and public agencies can influence the innovation processes through their strategies and policies.

SIs are not ‘machines’ that produce innovations in a mechanical or automatic way. They are systems in which the different activities are partly self-organized. Part of this coordination is performed by the self-organization of markets. And another part of the necessary coordination of the activities is achieved by means of policy and politics—as we will discuss in Chapter 3, and in much of the rest of this book.

2.4 Key Activities in Innovation Systems

No consensus has yet emerged among innovation researchers as to which specific activities (functions, determinants) should be included. This is because innovation research has not yet been able to identify in a specific enough manner the determinants of the development and the diffusion of different kinds of innovation. The state of the art is simply not advanced enough—and this provides abundant opportunities for further research. In Box 2.2 we present a hypothetical list of ten activities. This list of activities is based on the literature and on our own knowledge about innovation processes and their determinants, as discussed earlier (Edquist, 2005; Edquist and Chaminade, 2006; Chaminade and Edquist, 2010 and Edquist 2011). The activities are not ranked in order of importance, but the list is structured into four thematic categories:

  1. I. Provision of knowledge inputs into the innovation process (e.g. research, education, training, and competence development).

  2. II. Demand‐side activities (e.g. public procurement for innovation, or articulation of new product quality, or safety requirements).

  3. III. Provision of constituents of SIs, for example creating and changing organizations (e.g. entrepreneurship), creating and changing institutions, networking, and interactions.

  4. IV. Support services for innovating firms (e.g. financing innovation processes or incubation of innovative firms).

The different activities can each be considered to be determinants of the development and diffusion of innovations. The list is certainly preliminary. (p.25) Extra activities may be added as our knowledge about determinants of (different kinds of) innovation processes increases.

Our specific definition of innovation systems (presented in general terms in Section 2.3) is based on a particular specification of the SI approach where the ten activities (or determinants of innovation processes) define an innovation system. This definition of an SI is much broader and more general than other variants (e.g. Lundvall’s and, especially, Nelson and Rosenberg’s).9 (p.26) It includes all determinants of innovation processes (as well as the innovations themselves).

The concept of ‘innovation ecosystem’ is increasingly used. As we see it, the biological analogy ‘eco’ adds nothing of substance at all. This is pointed out by other authors, who also claim, ‘Innovation ecosystems is not yet a clearly defined concept, much less a theory. Moreover, the idea carries pitfalls, notably its over-emphasis on market forces, and its flawed analogy to natural ecosystems’ (Oh et al. 2016, p. 1). Our activities approach to SIs is a more clearly defined notion, and much more useful as a basis for pursuing innovation policy (as we will see in Chapter 3).

It is important to keep in mind that the activities are not ranked according to importance. Together, they all refer to different dimensions of determinants of innovation processes, which complement each other in different ways—sometimes potentially overlapping and reinforcing each other, sometimes pulling in different directions.

The list of activities (sometimes called functions in other lists) in Box 2.2 is preliminary, and one among several possible lists of activities. It will certainly be revised when our knowledge of the determinants of innovation processes has improved. Nonetheless, this list can still be used as a checklist or signpost to discuss the factors that—probably—affect innovation processes. This is important, as innovation processes are very complex and influenced by a variety of factors. Among other things, the list can serve as a tool to avoid simplistic mono-causality, i.e. an overly strong emphasis on one single activity (be it research or seed funding) and a neglect of others (be it innovation-enhancing public procurement or entrepreneurship). Innovation processes are certainly multicausally determined, i.e. partially influenced by several or many activities or determinants. This is important when we causally try to explain innovation processes and when we want to select innovation policy instruments to mitigate policy problems (see Chapter 3).

The list in Box 2.2 may thus be useful in assigning causes to policy problems and to identify possible policy instruments to solve the policy problems. If the main cause of a policy problem is a lack of research, then R&D should be in focus. If the cause is a lack of demand for certain kinds of product innovation, then a demand-side instrument such as innovation-enhancing public procurement can be used. At least the most important causes of the development and diffusion of innovations need to be identified, in order for policy-makers and politicians to be able to identify innovation policy instruments that can solve or mitigate the policy problems. All ten activities in Box 2.2 can be related to several innovation policy instruments. In fact, several instruments might have to be considered for each of the ten activities in the innovation system, i.e. it can even be a matter of choosing from among scores of instruments (Borrás and Edquist, 2013b, and Chapter 11 in this book).

(p.27) Therefore, our approach is broader than corresponding approaches because we focus on all the activities in SIs (rather than on the components in the systems). Furthermore, it is dynamic because we focus on the changes associated with determinants. For example, we address ‘creating and changing organizations’ and ‘creating and changing institutions’, rather than organizations and institutions as such in the list of activities (see Box 2.2). Our focus on ‘activities’ emphasizes strongly what happens in the systems—rather than their components. In this sense the activities approach provides a more dynamic perspective than other perspectives, such as Lundvall’s and Nelson and Rosenberg’s.

We believe that understanding the dynamics of each of the activities and the division of labour between private and public organizations in performing them is important to describe, explain, and influence innovation processes. It is a useful departure point for discussing the role of the state (public organizations) in influencing the direction and speed of innovation processes by means of innovation policies.

The list of ten activities is an effort to organize the determinants of innovation processes in SIs. The list should be seen as an effort to theorize about determinants of innovations in innovation systems. In other words, the list is a theoretical effort to create some order in a number of determinants of innovations previously identified by the rich literature of evolutionary and institutional economics of innovation.

2.5 Specification of the Activities in Systems of Innovation

In this section we will describe in more detail some of the activities listed in Box 2.2.

2.5.1 Provision of Knowledge Inputs to the Innovation Process

2.5.1.1 Provision of Research and Development Results

‘Research and experimental development (R&D) comprise creative work undertaken on a systematic basis in order to increase the stock of knowledge, including knowledge of man, culture, and society, and the use of this stock of knowledge to devise new applications’ (OECD, 2002, p. 30). According to the Frascati Manual, the term R&D covers three activities: basic research, applied research, and experimental development. Basic research is experimental or theoretical work undertaken primarily to acquire new knowledge without any particular application or use in view. Applied research is also original investigation in order to acquire new knowledge, but is directed (p.28) mainly toward a specific practical aim or objective. Experimental development is systematic work, drawing on existing knowledge gained from research and/or practical experience, which is directed to producing new materials, products, or devices, to installing new processes, systems, and services, or to improving substantially those already produced and installed (OECD, 2002, p. 30).

Here, we want to distinguish, to the largest possible extent, between determinants of innovation processes and innovation processes as such. Obviously, ‘Experimental development’, according to the Frascati definition, highly overlaps with innovation activities.

R&D results are an important basis for some innovations, particularly radical ones in engineering, medicine, and the natural sciences. R&D resulting in radical innovations has traditionally been an activity partly financed and carried out by public organizations. This applies to basic research, as well as to applied research in some countries, conducted in public universities and public research organizations. NSIs can differ significantly with regard to the balance between these two kinds of organization in the provision of R&D. In Sweden, less than 5 per cent of all R&D is carried out in public research organizations. In Norway, this figure is more than 20 per cent.

Such data may be a way of distinguishing between different types of NSIs. In most low- and medium-income NSIs in the world today, little R&D is carried out and the bulk of this is performed in public organizations. Some high-income countries spend considerable amounts of their GDP on R&D, and much of that is carried out by private organizations. This includes not only some large countries such as the USA and Japan, but also some small- and medium-sized countries such as Sweden, Denmark, Switzerland, and South Korea.

Because innovation processes are evolutionary and path dependent, there is a danger of negative lock-ins, that is, trajectories of innovation that lead to low growth and decreasing employment. Potentially, superior innovation trajectories may not materialize and the generation of diversity may be reduced or blocked. In such situations, the state should favour experimentation and use R&D subsidies and public procurement for innovation, for instance, to support possible alternatives (Edquist et al., 2004).

In sum, public organizations may influence the R&D activity in different ways ranging from allocating funds for specific research activities in public universities and research centres to stimulating alternatives via R&D subsidies. However, more analysis is needed in order to understand the inter-relationships of R&D, innovation, productivity growth, the role of R&D in (p.29) innovation in different sectors, and the impact of different instruments on the propensity of firms to invest in R&D.

2.5.1.2 Competence-Building

Here we use the definition of (Johnson et al., 2002) of competence-building that includes formal education and training, the labour market dynamics, and the organization of knowledge creation and learning within firms and in networks. Knowledge is a ‘stock’ category and learning is a ‘flow’ category adding more knowledge to the existing ‘stock’. Competence-building includes processes and activities related to the capacity to create, absorb, and exploit knowledge for individuals and organizations. Obviously, this includes formal learning as well as informal learning.10 In addition, informal learning is vital for innovation processes and, therefore, an important part of (the activity of competence-building in) SIs.

n most countries, much of the education and training that are important for innovation processes (and R&D) are primarily provided by public organizations—schools, universities, training institutes, and so on. However, some competence-building is done in firms through learning-by-doing, learning-by-using, and learning-by-interacting—which are informal activities. Competence-building may increase the human capital of individuals: that is, it is a matter of individual learning, the result of which is controlled by individuals.11

The organizational and institutional contexts of competence-building vary considerably among NSIs. There are, for example, significant differences between the systems in the English-speaking countries and continental Europe. However, scholars and policy-makers lack good comparative measures on the scope and structure of such differences. There is little detailed knowledge about the ways in which the organization of education and training influences the development and diffusion of innovations (Toner and Woolley, 2016; Lorenz et al., 2016; Lorenz, 2011). As labour, including skilled labour, is—still—the least mobile production factor, domestic systems (p.30) for competence-building remain among the most enduringly national of elements of NSIs. However, international mobility of labour is in the process of increasing.

Competence-building should not, however, be limited to human capital. Organizations may have competences that exceed those of the employees.12 Human capital is hired by the company but is always owned by individuals. There are ways in which the firm can capture individual knowledge and transform it into organizational knowledge. There is also learning at the social level, i.e. neither individual nor organizational learning, but involving society outside these spheres. Organizing the processes of learning within the firm and in networks is part of the competence-building activity (Lundvall et al., 2002). Many individuals belong to many networks, both formal and informal, where learning takes place. Individuals may have attachments other than employment organizations, such as labour unions, technical societies, and Rotary Clubs. Scholars started to analyse such processes in the late 1990s, but many questions remain unanswered (Edvinsson and Malone, 1997; Lorenz and Lundvall, 2011).

2.5.2 Demand-Side Activities

2.5.2.1 Formation of New Product Markets

In the very early stages of the development of new fields of innovation, there is uncertainty about whether market demand exists.13 The state might need to intervene in the market from the demand side for market creation (Mazzucato, 2016). There are two main reasons for this: a market for certain goods and services might not exist, or the users of goods and services might not be sophisticated enough to provide the required feedback to the producers with regard to new needs.

One example of market creation is in the area of inventions. The creation of intellectual property rights (IPR) through patents gives a temporary monopoly to the patent owner, which is intended to enhance commercialization by making the selling and buying of technical knowledge easier.14 Policy-makers may also enhance the creation of markets by supporting legal security or the formation of trust.

(p.31) Another example of public support to market creation is the creation of standards. For example, the NMT 450 mobile telecom standard created by the Nordic telecommunication companies in the 1970s and 1980s—when they were state-owned monopolies—was crucial for the development of mobile telephony in the Nordic countries. This made it possible for private firms to develop mobile systems (Edquist, 2003).

In some cases, the instrument of public procurement for innovation has been important for market formation (Edquist et al., 2000b, 2014; Edquist and Zabala-Iturriagagoitia, 2012, 2015; Edquist, 2014c, 2015). In other words, a market emerged because the public sector demanded products and systems that did not exist before the public procurement for innovation. This has been—and still is—an important instrument in the defence sector in all countries. It has also been important in infrastructure development (telecoms, trains, etc.) in many countries. Moreover, public policy may influence demand—and thereby diffusion of innovations—when public agencies require a certain product mix, such as a minimum share of electricity based on renewable resources or cars powered by electricity or fuel cells.

The provision of new markets is often linked to the articulation of product quality requirements. Articulation of quality requirements emanating from the demand side with regard to the characteristics of the new products is important for product development in most SIs, enhancing innovation and steering processes of innovation in certain directions (see Sections 3.5 and 3.6 for a discussion of the meaning of the term ‘direction’). Most of this activity is performed spontaneously by demanding customers in SIs, as a result of interactive learning between innovating firms and their customers. However, product quality requirements may also be a consequence of public action, for example, regulation in the fields of health, safety, and the environment, or the development of technical standards. Public procurement for innovation normally includes a functional specification of the product or system wanted, and this certainly means demand articulation that influences product development significantly.

Functional procurement can be defined as the procurement of products by a public authority/unit that describes a function to be performed (or a problem to be solved) instead of describing the product that is to perform the function. In functional procurement, a public agency specifies what is to be achieved rather than how it is to be achieved. Functional regular procurement is pursued by means of functional specifications instead of product specifications. Hence, it is a matter of the manner in which a procurement call is set up and the tender documentation is formulated. Needs are translated into functions to which potential suppliers can respond. Needs are accurately identified and presented as requirements in terms that suppliers can respond to. It opens up for innovation but does not require it. Innovations are not excluded or disadvantaged, as they are in product procurement.

(p.32) 2.5.3 Provision of Constituents for Systems of Innovation

2.5.3.1 Creation and Change of Organizations

As pointed out, organizations are considered key components in SIs. Entry and exit of organizations, as well as change of incumbent organizations, are therefore important activities contributing to the change of SIs as such. Organizations include not only firms, but also universities, research institutes, financing bodies, and so on. But since firms are ultimately responsible for commercializing new products, we will focus mainly on the creation and change of firms.

The creation and change of organizations for the development and diffusion of innovations is partly a matter of spontaneous firm-creation (through entrepreneurship) and diversification of existing firms (through intrapreneurship). However, public action can also facilitate such private activities by institutional change, for example, by changing tax laws. Mergers between firms are also organizational changes. New R&D organizations (public research organizations and universities) as well as innovation policy agencies are also created through political decisions.

One important role of policy is to enhance the entry and survival of new firms by facilitating and supporting entrepreneurship. Compared to incumbents, new entrants are characterized by different capabilities, and they may be the socio-economic carriers of innovations. They bring new ideas, products, and processes. Hence, public agencies should create an environment favourable to the entry of new firms and the growth of successful small and medium-sized firms. Survival and growth of firms often require continuous (or at least multiple) innovations, particularly in high-tech sectors of production.

Enhancing entrepreneurship and intrapreneurship may be a way of supporting changes in the production structure in the direction of producing new products to a larger extent. There are three mechanisms by which the production structure may change through the addition of new products: existing firms might diversify into new products (as has happened often in Japan and South Korea, for example); new firms in innovative product areas might grow rapidly (as many have in the USA, for example); foreign firms might invest in new product areas in a country (Ireland, for example).

Adding new products to an existing bundle of products is important, since the demand for new products might grow more rapidly than for old ones—with accompanying job creation and economic growth. New products might also be characterized by high productivity growth. Public agencies could therefore create opportunities and incentives for changes in the production structure.

In any SI it is important to study whether the existing organizations are appropriate for promoting innovation. How should organizations be changed (p.33) or engineered to induce innovation? This dynamic perspective on organizations is crucial in our version of the SI approach (the systems activities approach). Creation, destruction, and change of organizations were very important in the development of strategies in the successful Asian economies and they are crucial in the ongoing transformation of Central and Eastern Europe and Latin America. Hence, organizational changes seem to be particularly important in situations of rapid structural change which, in turn, is linked to building the capacity to deal with such changes. Policy issues in this context concern how policy-makers may help develop alternative patterns of learning and innovation, and nurture emerging sectoral SIs (Edquist et al., 2004).

2.5.3.2 Interactive Learning, Networking, and Knowledge Integration

As we have pointed out, relations among SI components (i.e. organizations such as firms, universities, public agencies, and institutions such as established practices, rules, and laws) are a basic constituent of SIs. Relations facilitate interactive learning which, in turn, is a basis for innovation. The SI approach, emphasizing interdependence and non-linearity, is based on the understanding that firms normally do not innovate in isolation, but interact with other organizations through complex relations that are often characterized by reciprocity and feedback mechanisms in several loops. Innovation processes are not only influenced by the components of the systems, but also by the relations among them. This captures the non-linear features of innovation processes and is one of the most important characteristics of the SI approach.

The interactive nature of much learning and innovation implies that this interaction could be targeted much more directly than is normally the case in innovation policy today (Oerlemans and Meeus, 2005; Lundvall and Johnson, 1994). The SI approach should not only focus on the organizations of the systems, but also—and perhaps primarily—on the relations among them. Relations between organizations might occur through markets and other mechanisms. This implies integrating new knowledge developed in different spheres of SIs and coming from outside with knowledge already available in the innovating firms. It is a matter of ‘learning linkages’ across the boundaries of organizations.

Most of the interaction between organizations involved in innovation processes occurs spontaneously when there is a need. The activity of (re)combining knowledge—from any source—into product and process innovations is largely carried out by private firms by means of self-organization. They often collaborate with other firms, but sometimes universities and public research organizations are also involved. The long-term innovative performance of firms in science-based industries strongly depends on the interaction of (p.34) firms, universities, and research facilities. If they are not spontaneously operating smoothly enough, these interactions should be facilitated by means of policy. Here, institutions are important, as we will see in Section 2.5.3.3.

Relations between universities and public research institutes, on the one hand, and firms on the other are coordinated only to a limited degree by markets. Policies help coordinate relations in different ways and to different degrees, reflecting differences across NSIs—but sometimes they are not coordinated at all. Incubators, technology parks, and public venture capital funds might also help in a similar way. This means that the public sector might create organizations to facilitate innovation. At the same time, however, it might create the rules and laws that govern these organizations and their relations to private ones—that is, create and change institutions (Edquist et al., 2004).

2.5.3.3 Creation and Change of Institutions

Institutions are normally considered the second main component in SIs, in addition to organizations. Creating, demolishing, and changing institutions are crucial to the maintenance of SIs’ dynamism. Important institutions in SIs are IPR laws, procurement regulations, technical standards, tax laws, environment and safety regulations, R&D investment routines, procurement rules, firm-specific rules and norms, and many more. They influence innovating organizations and innovation processes by providing incentives (or obstacles) to organizations and individuals to innovate.

IPR laws are considered important as a means of creating incentives to invest in knowledge creation and innovation (and, as argued earlier, they create markets). We have already mentioned the important role of institutions in facilitating the interaction of organizations in Section 2.5.3.2. Public agencies may, for example, support collaborative centres and programmes, remove barriers to cooperation, and facilitate the mobility of skilled personnel among different organizations and regions (Edler et al., 2011). This might include the creation or change of institutional rules that govern the relations between universities and firms, such as the one in Sweden stating that university professors shall perform a ‘third task’ in addition to teaching and doing research: that is, interact with the society surrounding the university, including firms (Edquist et al., 2004) and wider society as well (Tsipouri, 2012). There are institutions that influence firms and there are institutions that operate inside firms (for taxonomies of institutions see Edquist and Johnson, 1997).

Some institutions are created by public agencies. They are often codified and constitute policy instruments (such as the aforementioned IPR laws). Public innovation policy is partly a matter of formulating the rules of the game that will facilitate innovation processes. These rules might have nothing to do with markets, or they might be intended to create markets or make the operation of (p.35) markets more efficient. Many institutions (such as laws and regulations) are publicly created and therefore easy to modify by governments. However, others are created by private organizations, such as through firms’ routines, norms, and culture. They develop spontaneously over time and are much more difficult to influence by public agencies.

As in the case of organizations, it is important to study whether the existing institutions are appropriate for promoting innovation and to ask the same question of how institutions should be changed or engineered to induce innovations of certain kinds. Here, too, the evolution and design of new institutions were very important in the development strategies of the successful Asian economies and in the ongoing transformation of Central and Eastern Europe and Latin America. Hence, again, institutional (as well as organizational) changes are particularly important in situations of rapid structural change.

2.5.4 Support Services for Innovating Firms

2.5.4.1 Financing of Innovation

Financing of innovation processes is absolutely crucial for turning knowledge into commercially successful innovations and to facilitate their diffusion. The significance of the financing of innovation processes is certainly not reflected in the space it receives here—and the heading ‘support services’ is not intended to downgrade its importance. Financing comes primarily from private actors within innovating firms (internal capital markets), stock exchanges, venture capital funds, equity firms, banks, or individuals (‘business angels’). However, in many countries—including the USA—public agencies provide financing in the form of seed capital, for instance, in support of innovation activities.

As with public intervention in general, public funds (financial subsidies) should only come forward when firms and markets do not spontaneously perform this activity well enough (for example, when there is uncertainty or when risk is too great). But the question is not just when the public sector should finance innovation activities but also how: that is, what should be the instruments and what should be the appropriate balance between public and private funding in a particular SI.

2.5.4.2 Incubating Activities

Incubating activities include the provision of access to facilities and administrative support for new innovating efforts. In recent decades, incubating activities have been carried out in science parks to facilitate the commercialization of knowledge. That this activity has become partly public has to do with the uncertainty characterizing early stages of product development, which means that markets do not operate well in this respect. In addition, (p.36) universities have started their own incubating activities to commercialize the results of their research activities.

However, innovations are also emerging in existing firms through incremental innovation and when they diversify into new product areas. In those cases, the innovating firms normally provide incubation themselves. There is a need to better understand the conditions under which incubation needs to be a public activity and when it should be left to the private initiative.15

Notes:

(1) Organizational innovations here capture forms within the production process, as they correspond to technological innovations—it is not meant to capture new organizations, such as firms or public agencies.

(2) Note that ‘process innovations’ are not the same as innovation processes’, used later.

(3) This definition is based on the 2005 edition of the OECD Oslo Manual, which is the standard basis for work on innovation within the OECD and the EU—and elsewhere. During the phase of the work with this book when we checked the copy editing (late October 2018), the Oslo Manual 2018 was published. The following is a quote from the OECD trailer: ‘The Oslo Manual distinguishes between innovation as an outcome (an innovation) and the activities by which innovations come about (innovation activities). This edition defines an innovation as “a new or improved product or process (or combination thereof) that differs significantly from the unit’s previous product or processes that has been made available to potential users (product) or brought into use by the unit (process)”’; http://www.oecd.org/sti/inno/oslo-manual-2018-info.pdf. We decided to make no changes in the text of this book caused by the new edition. However, we want to point out the following:

  • () The Oslo Manual 2018 definition of innovation is more similar to the definition in this book than to definitions in previous editions of the Oslo Manual.

  • () It is interesting that the new Oslo Manual talks about innovation ‘activities’.

  • () To qualify as an innovation the new product or process must have been made available to users.

(4) It might also be useful to distinguish between incremental and radical innovations and between science-based and experience-based innovations. A general remark is that the notion of innovation in a general sense is so comprehensive and heterogeneous, that it is useful to create various taxonomies of innovation and deal with the different categories of innovation separately, when describing and explaining innovation processes. However, different taxonomies will not be discussed in any detail here.

(5) Innovation systems cannot be internal to (large) firms, but firms are the most important organizations in innovation systems.

(6) What follows in the rest of this section is based on Edquist 2014b.

(7) To study the relations between them, they must be conceptually distinguished from each other. For Nelson and Rosenberg (1993), ‘institutions’ are the same as different kinds of ‘organizations’ (‘players’), while the term ‘institution’ primarily means ‘the rules of the game’ for Lundvall (1992). Hence, the term ‘institution’ is used in different senses in the literature, and institutions and organizations are often not clearly distinguished from each other.

(8) The focus on activities here does not mean that we disregard or neglect the organizations and institutions that constitute the components of SIs. When addressing activities it is also necessary to address the organizations (or organizational actors) that carry out these activities and the institutions (institutional rules) that constitute incentives and obstacles affecting the innovation efforts of these organizations.

(9) Nelson and Rosenberg’s definition, organizations that support R&D, is actually very close to being linear.

(10) Formal learning is planned learning resulting from activities within a structured learning setting; it often takes place within a teacher–student relationship, such as in a school system. Informal learning occurs outside formal learning and teaching settings, often through the experience of day-to-day situations. It is a part of ‘lifelong learning’, extending for decades after formal schooling. Formal learning is often a foundation for informal or ongoing learning.

(11) There is also organizational learning, the result of which is controlled or owned by firms and other organizations. Organizational learning leads to the accumulation of ‘structural capital’, a knowledge-related asset controlled by firms (as distinguished from ‘human capital’). An example of such an asset may be a patent, based on learning pursued by individuals but often owned by firms. Organizations have an interest in transforming individual knowledge into organizational knowledge, e.g. through codification of individual knowledge into operation manuals (Edquist et al., 2001b).

(12) Of course, the competence of an organization may also amount to less than the sum of the individual competencies, the organization thereby being dysfunctional.

(13) In this sub-section we will address ‘Formation of new product markets’ as well as ‘Articulation of product quality requirements’ (see Box 2.2).

(14) Paradoxically, then, a monopoly is created by law in order to create a market for knowledge: that is, to make it possible to trade in knowledge.

(15) In this book we include the discussion of incubation activities when addressing Financing of innovation. In addition, we choose not to discuss Provision of consultancy services at all in this book (see Box 2.2).