Innovation, Regional Development and the Life Sciences

Beyond clusters

Kean Birch

• Publisher: Routledge
• Year: 2016
• Print ISBN: 9781138807617
• eBook ISBN: 9781317613817
• Edition: 1
• Topic: Business
• Subtopic: Business General
• Index: Business

The life sciences is an industrial sector that covers the development of biological products and the use of biological processes in the production of goods, services and energy. This sector is frequently presented as a major opportunity for policy-makers to upgrade and renew regional economies, leading to social and economic development through support for high-tech innovation.

Innovation, Regional Development and the Life Sciences analyses where innovation happens in the life sciences, why it happens in those places, and what this means for regional development policies and strategies. Focusing on the UK and Europe, its arguments are relevant to a variety of countries and regions pursuing high-tech innovation and development policies. The book's theoretical approach incorporates diverse geographies (e.g. global, national and regional) and political-economic forces (e.g. discourses, governance and finance) in order to understand where innovation happens in the life sciences, where and how value circulates in the life sciences, and who captures the value produced in life sciences innovation.

This book will be of interest to researchers, students and policy-makers dealing with regional/local economic development.

1 Introduction

Knowledge economies everywhere!

Introduction

Countries in the Global North have experienced significant upheavals in their industrial structure over the last few decades; most other countries have experienced similar dramatic changes. Since the mid-20th century various national governments, especially in the Global North, have supported policies and treaties to reduce tariffs and controls on international trade and investment. As a result, countries have had to adapt to new political-economic imperatives, especially in terms of global competition. Various academic geographers like Storper (1997), Scott (2000a, 2000b) and Dicken (2003) have argued that this globalization of the world’s political economy has meant that local and regional political economies are increasingly important sites for understanding national competitive advantage, itself a concept developed by the management theorist Michael Porter (1990).

In this context, declining manufacturing production, output and employment in the Global North – see Williams (1992) for example – has necessitated the re-invigoration of local and regional political economies through the development of geographical capacities relating to service and knowledge-based sectors in which innovation plays a central role. Rather than relying on manufacturing as the base of their national economies, which characterized post-Second World War Fordism (Jessop 2002), the argument goes that these countries have had to find ways to capture value from the so-called ‘knowledge-based economy’ or face continual decline (e.g. OECD 1996; European Council 2000). A number of commentators have lauded the emergence of this ‘new economy’ (Reich 1991), ‘knowledge economy’ (Leadbeater 1999), or ‘creative economy’ (Florida 2002), arguing that it is opening up new forms of organization, new forms of production and consumption, new forms of work, and so on.

The changing industrial structure of these countries has been defined in numerous ways, as just alluded to above. Stretching back to the 1970s, scholars like Daniel Bell (1973) argued that we are entering a ‘post-industrial society’ characterized by increasing knowledge intensity and turn towards service and professional work. More recent scholars have argued that the 1980s witnessed the transition from Fordism to Post-Fordism in which mass production and consumption were replaced with ‘flexible specialization’ (Piore and Sabel 1984), ‘network society’ (Castells 1996), or ‘neo-Schumpeterianism’ (Jessop 2002). Considering that scholarly debates in this area are long-standing and wide-ranging, it would be difficult to do justice to them here, but others have noted the varied and diverse ways in which this restructuring has been conceptualized. In particular, Benoit Godin (2006a) provides a detailed discussion of the many different ‘buzzwords’ used over the years from Bell’s ‘post-industrial society’ through Post-Fordism to ‘information society’. Similarly, Martin Sokol (2004) critically engages with a range of these concepts in his work, outlining the ambiguities and contradictions inherent in many of them.

With this in mind, it is important to note that while long-term trends show that manufacturing has declined precipitously in the Global North since the 1960s, the fact that this has been highly uneven geographically means that it might not be as simple as the dominant narrative suggests. For example, the UK started to de-industrialize in 1960, well before global competitive pressures were supposedly exerting their influence; countries like Spain and Portugal had relatively stable manufacturing sectors well into the 1990s; and even today Germany is still the world’s dominant manufacturing exporter despite competition from countries like China with significantly lower labour costs (Williams 1992; Hudson 1999; Dicken 2003). It is not that manufacturing in the Global North has hollowed out and been replaced by bright, shiny new high-tech sectors as the result of global market imperatives, but rather that different countries have faced different pressures and adapted in different ways to these pressures. Moreover, this restructuring has been explicitly localized and regionalized in that it has differed geographically both across and within countries. Some regions have witnessed rising manufacturing employment, others declining manufacturing but rising services employment, and others still have simply experienced ongoing and debilitating decline overall (Birch and Mykhnenko 2009).

Economic change is ongoing, it does not end. As a consequence it is always an important object of inquiry. This book is an attempt to understand these changes by examining the emergence of one particular high-technology sector (i.e. the ‘life sciences’) in one particular country (i.e. the UK). It is concerned with the growing emphasis on innovation and high-tech sectors as important contributors to regional development and renewal; the emphasis on the importance of the ‘local’ in academic and policy debates; and what this means for understanding the relationship between geography and innovation in the so-called knowledge-based economy on which we all supposedly depend for our future standard of living.

What is the knowledge economy?

What is the knowledge economy? What does it mean for society? A good starting point to answer these questions are the ongoing academic and policy debates on the role of knowledge and innovation to societies in the Global North. Most countries now have specific research and innovation policies that outline the particular government’s perspective on what knowledge and innovation represent, and most take a rather simplistic approach to these concepts (e.g. Government of Canada 2014; HM Treasury 2014). When I call them ‘simplistic’ I mean that they adopt a narrow approach to understanding the political economy of research and innovation. For example, the UK government’s 2014 science and innovation policy, Our Plan for Growth, is premised on a particular political-economic understanding of research and innovation:

If we are to become a flourishing knowledge economy, we have to build on our long-standing scientific advantages and innovate. But innovation requires investment. Countries around the world recognise that science and innovation is the right path for sustainable growth… Our ability to develop and commercialise new ideas, products and services is critical to our economic future and to providing jobs. Investment in our knowledge base is a crucial challenge for both government and business.

(HM Treasury 2014: 8–9)

In this policy narrative, research produces knowledge which is then turned into innovation – defined as new products and services – in a linear pathway. As many scholars have noted, however, this linear perspective of research and innovation is deeply problematic on a number of fronts (e.g. Gibbons et al. 1994; von Hippel 2005; Godin 2006b; Felt et al. 2007). Here I mention two problems with the linear view, but there are others.

First, knowledge has become a big deal in academic and policy debates about industrial restructuring because it is often thought of as a social or public good with few limits to its use; it is frequently treated as a commons on which we can all draw equally and seamlessly. As critical scholarship by the likes of Philip Mirowski (2011) and David Tyfield (2012a, 2012b) has shown, this perception pervades the work of early economists of science (e.g. Robert Solow, Kenneth Arrow) and has been particularly influential ever since (also see Godin 2006b). Subsequent work on the economics of science has reinforced these assumptions, largely for political reasons relating to the legitimation of rising science spending post-Second World War. More recent literature outside of mainstream economics has problematized the idea that knowledge is freely available, easily acquired, and easily integrated into organizational processes and routines (e.g. Cohen and Levinthal 1990; Howells 2002; Nightingale 2003). In part, this later literature has focused conceptually on the problem of tacit knowledge, a distinction originally made by Michael Polanyi (1958) to distinguish between formal, explicit and codified forms of knowledge (e.g. patent) and embodied, experiential and non-verbal forms of knowledge (e.g. the ability to balance). In this sense, the knowledge economy is characterized by the interaction between different forms of knowledge, as well as different attempts to capture that knowledge in useful forms.

Second, knowledge is not as easy to define as policy-makers would like, nor is the notion of a knowledge economy as simple as it sounds. A number of scholars conceptualize knowledge and the knowledge economy in ways that contradict the linear view mentioned above. Several examples spring to mind here: first, Lundvall (1992) argues that knowledge is simply a resource, while learning is the process we should focus on when considering the emergence of a ‘knowledge economy’; second, Ibert (2007) argues that it is better to theorize knowledge in terms of ‘knowing’ since this focuses on social practice rather than more abstract entities (e.g. patent); and third, Fuller (2002), in his work on social epistemology, argues that knowledge is a social process, rather than something that originates inside someone’s head. It is social in the sense that it necessitates social institutions (e.g. language) to undertake in the first place; social relations to be shared (e.g. dissemination); social practices to be produced (e.g. collaboration); and so on. As all these examples suggest, knowledge can be better thought of as a range of entangled social practices, processes and performances; consequently, the knowledge economy is better thought of as similarly messy – that is, collaborative, competitive, unidirectional, bidirectional, etc. all at once.

Why innovation?

We can ask a similar set of questions when we think about innovation. What is innovation? What does it mean for society? Whatever conception of knowledge or the knowledge economy we ascribe to, most people view innovation as an unalloyed social good. By this I mean that most people now see innovation as the source of economic, social and ecological development. This assumption is most obvious in the European Union’s (EU) new research and innovation strategy, Horizon 2020, which replaces the previous Lisbon Agenda (2000–2010), and runs from 2010 until 2020 (Birch and Mykhnenko 2014). The new EU strategy is sub-titled ‘a strategy for smart, sustainable and inclusive growth’ and includes flagship programmes like ‘Innovation Union’ designed:

… to improve framework conditions and access to finance for research and innovation so as to ensure that innovative ideas can be turned into products and services that create growth and jobs.

(CEC 2010: 3)

In this policy narrative, innovation is presented as the solution to a range of societal problems, which ends up naturalizing market-based approaches to social issues as diverse as youth unemployment, social exclusion and climate change.

The reason that innovation naturalizes market conceptions of the world is because innovation is frequently conceptualized in Schumpeterian terms as the commercial introduction of new technological products and services (Freeman 1974; Simmie 2001). This definition is prevalent in the field of innovation studies, especially research following the tradition established by people like Christopher Freeman (1974) who established the Science Policy Research Unit (SPRU) at Sussex University. However, Godin (2015) argues that this definition is ‘putting words into Schumpeter’s mouth’ since Schumpeter never defines innovation in these specific, commercial terms. Rather, Godin argues that Schumpeter was more concerned with the recombination of factors of production. Despite Godin’s argument otherwise, innovation is still largely conceptualized as the commercialization of research and knowledge in mainstream academic debate. This is evident in the terminology deployed by the journal Research Policy – the preeminent innovation studies journal – in its aims and scope:

Research Policy (RP) is a multi-disciplinary journal devoted to analyzing, understanding and effectively responding to the economic, policy, management, organizational, environmental and other challenges posed by innovation, technology, R&D and science. This includes a number of related activities concerned with the creation of knowledge (through research), the diffusion and acquisition of knowledge (e.g. through organizational learning), and its exploitation in the form of new or improved products, processes or services. [emphasis added]

Thinking of innovation as commercialization of knowledge does have some benefits, though, in that it helps to differentiate innovation more clearly from research and...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Dedication
• Table of Contents
• List of figures
• List of tables
• Acknowledgements
• List of abbreviations
• 1 Introduction: knowledge economies everywhere!
• 2 Innovation, clusters and knowledge-based commodity chains
• 3 Innovation geographies in the UK life sciences
• 4 Innovation governance in the Scottish life sciences
• 5 Innovation imaginaries in the European life sciences
• 6 Innovation financing in the global life sciences
• 7 Conclusion: innovation and regional development for whom?
• Index