Globalisation, New and Emerging Technologies, and Sustainable Development

The Danish Innovation System in Transition

Jesper Lindgaard Christensen, Birgitte Gregersen, Jacob Rubæk Holm, Edward Lorenz, Jesper Lindgaard Christensen, Birgitte Gregersen, Jacob Rubæk Holm, Edward Lorenz

• Publisher: Routledge
• Year: 2021
• ISBN:
  9781000368765
• Edition: 1
• Topic: Business
• Subtopic: Sviluppo di business
• Index: Business

This book explores the capacity of the Danish innovation system to respond to key societal challenges including the green imperative of achieving growth with environmental sustainability and the need to adapt to new and possibly disruptive changes in technology, often referred to as the Fourth Industrial Revolution.

The book is divided into four main parts. The first describes the evolving characteristics of the Danish system of research and innovation with special attention to the role of policy at the national and regional levels. The second part focuses on interorganisational relations, including the position of Danish firms in national and global value chains. The third part examines changes in labour markets and in the educational and training system, and it considers the impact of new technologies including robotics and artificial intelligence on employment and skills. The fourth part turns to issues of climate change and environmental sustainability including an assessment of the Danish economy's success in meeting the challenges of the UN Sustainable Development Goals.

The book will be of particular interest to small countries, of which the Danish innovation system is representative, but it also appeals more broadly to an audience interested in innovation systems and policies to support economic development.

Part I

The systems approach and policy agenda

1 The emergence of innovation policy as a field

The international context and the Danish experience

Jesper Lindgaard Christensen and Jan Fagerberg

1.1 Introduction

This chapter traces the development of scholarly interest in innovation and innovation policy in the Western world in general and in Denmark in particular, ranging from the early post-war period to the early years of the new millennium (Christensen and Knudsen 2021 for an account of more recent innovation policy developments in Denmark). Whereas we take a broad view of innovation and innovation policy, we do give special attention to the development of systems views on policy.

Today, innovation policy has become a part of the standard political vocabulary, but this was not always the case. In the early post-war world, it was common to view innovation as applied science, and science policy received increased attention by both policymakers and scholars. In fact, there was more focus on inventions than on innovation, understood as the introduction to the market of technologically new products or the implementation of new production processes.¹ However, as explained in the second section of this chapter, it gradually became clear that there was more to innovation than science alone, and that the conditions under which firms were able to innovate and upgrade technologically also needed to be understood. As a result, a rich body of knowledge on innovation in firms, including its relationship with other societal factors, emerged,² and this, together with other developments, influenced policy. The increasing interest in innovation policy, particularly in Europe, was related to the spread of system approaches to the study of innovation and its effects (e.g., ‘national systems of innovation’), which became common in several European countries around the turn of the 20th century.

In the third section, the focus of the chapter shifts to Denmark, and how innovation policy instruments gradually evolved as a result of policy needs, changes in the understanding of innovation, business cycles and innovation policy development elsewhere. The evolution of empirical knowledge about innovation, of the conceptual and theoretical understanding of the phenomenon, and innovation policy practice in Denmark are also investigated. The final section of the chapter considers the lessons from the study for policy processes.

1.2 The evolution of innovation policy in the post-war period

How far back in history interest in – and experimentation with – innovation policy can be traced is an open question. Innovation is clearly not something new, and policy instruments that affect innovation, in one way or another, have existed for a long time but may not have been explicitly termed as innovation policy. Hence, the use of the concept of innovation policy is fairly recent. In fact, it only started to be systematically used by academics and policymakers in the early 1980s. One of the early proponents of innovation policy, Professor Roy Rothwell at the Science Policy Research Unit (SPRU) at the University of Sussex in the UK, described it as follows: ‘Innovation policy is essentially a fusion of science and technology policy (patents, technical education, infrastructural based pure and applied research) and industrial policy (investment grants, tariff policy, tax policy, industrial restructuring)’ (Rothwell 1982, p. 3). He went on to distinguish between three different types of ‘innovation policy tools’: ‘supply’ (financial support, for example), ‘demand’ (purchases), and what he called ‘environmental’, which referred to the legal and regulatory framework, amongst other things.

Figure 1.1 gives an idea of the prevalence of the policies (or rather the associated terms) that, according to Rothwell, took part in the ‘fusion’. As the figure shows, industrial policy was already a well-established term in the early part of last century. The term got a boost in the 1970s and early 1980s, a period when the growth of the capitalist world economy had slowed down considerably compared to the early post-war period, and many established industries in Western economies felt increasing competition from Japan, commonly regarded as a champion of industrial policy (Johnson 1982). However, from the mid-1990s onwards, the usage of the term declined steeply, as direct public interference with industry and individual firms in particular, which many associated with the term, gradually lost credibility. This can be seen as a result of the widely held view that industrial policy during the economic downturn in the late 1970s and early 1980s tended to support (and prolong the lives of) uncompetitive firms that would eventually go out of business anyway, rather than foster fertile ground for new growth. However, it was probably also a reflection of the political changes associated with political leaders such as Reagan and Thatcher (e.g., the turn to neoliberalism) that had taken place in leading capitalist economies in the preceding years.

Figure 1.1 The frequency of industrial, science and technology policy terms according to Google. Source: https://books.google.com/ngrams, accessed on November 23, 2019.

Science policy, by contrast, was virtually unheard of before the early 1960s, and the term ‘technology policy’ is of even more recent origin (Lundvall and Borras 2004). During the early post-war period, governments and public opinion in Western countries became gradually more aware of the important role science and technology played in economic and military spheres.³ This also led to the funding of research and data collection of relevance for the topic. The OECD’s scheme for how to collect data on R&D, the so-called ‘Frascati Manual’, appeared in 1962 (OECD 1962), and the first research centres at universities focusing on the issue, such as the Science Policy Research Unit ( SPRU) in the UK and the Research Policy Institute (RPI) in Lund (Sweden), emerged shortly afterwards.

The dominant perspective among observers during these early years was what later became known as ‘the linear model’ (Kline and Rosenberg 1986), which purports that economic growth stems from advances in science (Bush 1945). Based on this perspective, the challenge of policy is to ensure that scientific activity in universities, research institutes and firms is properly funded, and that scientific knowledge is disseminated. According to the arguments in favour of this model, policy is needed because the ‘public good’⁴ nature of scientific advance would result in a widening gap between private and social returns and lead rational actors (i.e., firms) to dramatically underinvest in R&D compared with what would be optimal for society as a whole (Nelson 1959; Arrow 1962).⁵ In order to alleviate negative effects on a country’s economy, various forms of public support for knowledge production and dissemination, such as universities, research institutes, technology transfer schemes, and intellectual property rights (IPR) systems may be justified.

While the ‘linear model’ has been, and continues to be, influential among academics and policymakers, it gradually became clear that the thinking underlying that model overlooked a number of important factors. In particular, it paid too little attention to the specific conditions under which firms search for, absorb, create and transform knowledge into goods and services, or in other words, innovate (Cohen 1995). This is perhaps understandable, as there was very little empirically supported knowledge on this subject available at the time. In fact, one of the first research projects initiated by the founding director of the SPRU, Christopher Freeman, aimed to fill this knowledge gap. The project, named SAPPHO, surveyed ‘success and failure in innovation’ in British firms (Rothwell et al. 1974). Another influential survey on innovation in firms, this time based on US data, was that of Levin et al (1987).⁶ Since the early 1990s, the so-called ‘Community Innovation Survey’ (CIS) has mapped innovation activities in European firms, and similar surveys have been conducted in other parts of the world (see Fagerberg et al. 2010 for an overview). These surveys – and the research to which they led – gave a more nuanced picture of innovation (Fagerberg 2004). For example, it turned out that innovative firms did not, for the most part, attach high importance to using legal means, such as patents, to fight off imminent threats from imitators, but instead focused on being first in the market. Explanations of these research findings emphasised several mechanisms allowing firms to profit from knowledge investment: knowledge may be contextual in nature, difficult to copy and exploit, dependent on various forms of complementary assets, etc. Moreover, rather than jealously guarding their secrets, the surveys and research that followed showed that firms cooperated extensively with other actors, especially customers (users) and suppliers, while universities – the main actors in the linear model – were used much less frequently as a direct collaboration partner for innovation.

In the early years of innovation research only a small number of researchers in a few universities and countries were taking part. However, during the decades that followed, societal as well as scholarly interest in innovation increased, and today many thousands of scholars worldwide are active in this area, which often falls under the umbrella of ‘innovation studies’ (Fagerberg and Verspagen 2009). The accumulation of information and knowledge about this phenomenon has been accompanied by theoretical developments, three of which deserve particular mention here. First, a new theory of knowledge-based firms and economic evolution, drawing on behavioural theory as well as the older contributions by Schumpeter (1934, 1942), was developed by Richard Nelson and Sidney Winter. Their 1982 book, An Evolutionary Theory of Economic Change, is the most cited work in innovation studies (Fagerberg et al. 2012). Second, in the tradition of Schumpeter, Christopher Freeman, Carlota Perez and others focused on the role that specific (revolutionary) technologies, particularly ICTs, played in fostering economic growth (Freeman et al. 1982; Freeman and Perez 1988; Freeman and Louçã 2001), paving the way for greater attention – particularly in the 1980s and 1990s – being given to ‘technology policy’ (Figure 1.1). Third, and possibly most important from a policy point of view, the findings from empirical innovation research on the interactive nature of innovation led to the development of a systems approach to innovation (Freeman 1987; Lundvall 1992; Nelson 1993), which particularly emphasised the interactions between the various actors and institutions in the system for the (innovation) performance of the system as a whole. Although the approach can be (and has been) applied at different levels of aggregation, the earliest and arguably most influential contributions in this research tradition focused on the national level, hence the term ‘national innovation system’ (NIS). This quickly attracted the interest of policymakers, not least because the OECD did a lot to propagate the approach during the 1990s and 2000s (OECD 1997, 1999, 2002). In this conceptual development, narrow and broad perspectives surfaced. The former, narrower perspective primarily focused on the R&D system of a country and the public organisations supporting it, whereas the broader perspective both included a wider array of formal institutions into the analyses, such as the education and training system and regulation of labour markets, and emphasised to a larger extent the informal institutions that facilitate the interactions between core agents in the system (Edquist 2004). These two perspectives lead to some extent to different policy implications.

Figure 1.2 illustrates the spread of the term ‘innovation policy’ and ‘innovation system’ over time. As the figure shows, the term was rarely used before 1980, and then often with a different meaning than it holds today.⁷ As mentioned, the term became more common in the early 1980s, when SPRU professor Roy Rothwell started to ...

Table of contents

• Cover
• Half-Title
• Series
• Title
• Copyright
• Contents
• List of figures
• List of tables
• List of contributors
• Preface
• Acknowledgements
• Introduction: Globalisation, new and emerging technologies and sustainable development – the Danish innovation system in transition
• PART I The systems approach and policy agenda
• PART II Value chains, innovation and inter-organisational relations
• PART III Technology, employee learning and the labour market
• PART IV Green transition and sustainability
• Index