Universities, Cities and Regions

Loci for Knowledge and Innovation Creation

Roberta Capello, Agnieszka Olechnicka, Grzegorz Gorzelak, Roberta Capello, Agnieszka Olechnicka, Grzegorz Gorzelak

• Publisher: Routledge
• Year: 2012
• eBook ISBN: 9781136221316
• Topic: Business
• Subtopic: Business General
• Index: Business

Regions and cities are the natural loci where knowledge is created, and where it can be easily turned into a commercial product. Regions are territories where, under certain socio-economic conditions, a strong sense of belonging and mutual trust develops the ability to transform information and inventions into innovation and productivity increases, through cooperative or market interaction. Especially in contexts characterised by a plurality of agents — such as cities or industrial districts — knowledge is the result of cooperative learning processes, nourished by spatial proximity, network relations, interaction, creativity and recombination capability.

This book explains the logic behind these interactions and cooperative attitudes in regions and cities. One of the most significant channels comes from the presence of a university and its collaboration with firms and scientific research centres. These mutual relations between academic institutions and enterprises are of key importance.

The significance of universities in driving economic well being and regional development has been well documented for some time now. Much of the research, however, has centred upon countries in Western Europe and the United States. Increasingly, and since the expansion of the European Union in 2004 in particular, themes of academic entrepreneurship, university-business links, knowledge and innovation have become important on a Europe-wide scale. This book draws together key thinkers from across the continent to analyze the importance of higher educational institutions in fostering development.

Part I

Universities

Local/regional institutions of knowledge creation and innovation in national and international contexts

1 Science-based activities in European regions

The knowledge-innovation nexus

Roberta Capello

1 Introduction¹

The decisive globalization processes that have taken place in the last decade have increasingly put economic actors and policy makers under severe stress, in search for ad hoc strategies and policies to support competitiveness. At the European level, encouraged by the Lisbon Agenda (March 2000), all policy levels are contributing to the reinforcement of innovation and to the creation of the knowledge economy. Knowledge has in recent years become a key driver of growth in economic systems; access to knowledge is generally considered as a key condition for innovative activities in our modern economy. The idea of knowledge as the main discriminating element in economic and social performance was pointed out even before the Lisbon Agenda by some national governments, such as the United Kingdom, where in 1998 a white paper on ‘Our Competitive Future, Building the Knowledge Driven Economy’ was produced by the Department of Trade and Industry.

The well-known European strategy defined in the Lisbon and Luxembourg ministerial meetings (2000 and 2005) engages the Union to become the most competitive and dynamic knowledge-based economy in the world. A complex indicator for regional achievement of the Lisbon performance was circulated in the Luxembourg meeting, concentrating on private R&D investment and expenditure, educational levels of the labour force and productivity levels. An increasing flow of public resources into the scientific research system was requested up to the economic crisis (mid 2008) and is likely to be consented to by public authorities, giving rise to a huge scientific engagement into the measurement of the internal efficiency, productivity and impact of the research system itself (Okubo 1997; Joly 1997) (Table 1.1).

At the beginning of the discussion most initiatives and policy suggestions were focused on the context of European or national economies, but it soon became evident that the same reasoning should have been applied at a more territorially disaggregated level of analysis, such as the regional level. A bottom-up approach in the development of the knowledge economy was thought to be interesting, given the high spatial concentration that innovation and knowledge creation activities were subject to. Clusters of technologically advanced firms, such as Silicon Valley in California, ‘Route 128’ in the Boston area, Baden-Württenberg in the South of Germany, Jutland in Denmark, Småland in Sweden, Sophia-Antipolis close to Nice, to cite only some examples, testified the presence of some form of increasing returns on the concentration of innovative activity.

Table 1.1 Average increase of R&D over GDP ratio over the period 1996–2007 in different countries

Countries	Average increase R&D/GDP 1996–2007
Australia	2.1
Brasil	2.6
China	8.2
India	1.9
Mexico	4.2
South Korea	3
Canada	1.8
France	1.6
Germany	-0.4
Italy	1.2
Japan	1.8

Source: World Bank and Eurostat data.

Different reasons were given for the importance of space in the creation of a knowledge economy: externalities stemming from the urban environment, knowledge spill-overs subject to strong and visible distance-decay effects, collective learning based on a relational space where economic and social interactions take place and are embedded into geographical space.

The new territorial approach links to the idea that knowledge develops and accumulates through slow individual and collective learning processes, and grows through information, interaction and local knowledge. Knowledge creation is therefore a local process, rooted in the historical development of the area, accumulated over time through experience, local culture in the local labour market and local context, and is therefore difficult to transfer elsewhere.

Based on these reflections, a large consensus was achieved in the scientific sphere about the fact that regional competitiveness – and consequently regional growth – was no longer dependent on the traditional production resource endowment, capital and labour. The hyper-mobility that nowadays characterizes these factors reduces their geographical concentration, and shifts the elements on which competitiveness rests from the availability of material resources to the presence of immobile local resources such as local culture, competence and innovative capacity; in general: knowledge.

In this spirit, even in recent times, in the Green Papers of the Territorial Cohesion and of the European Research Area, the European Commission has called for particular attention to the territorial dimension of innovation and knowledge creation. The diversity of innovation activities, of the spatial diffusion of innovation throughout the European territory, of the capacity of regions to create knowledge and to exploit knowledge from outside calls for an in-depth analysis of the territorial dimension of the knowledge economy, on which the so-called ‘third generation of innovation policy at Community level’ can rely.

As Danuta Hübner (2009: 2) claims:

innovation policy at community level is now moving into its third generation. It is moving away from the approach of the first generation of innovation policy which focused on R&D through a linear process for the development of innovations, beginning with laboratory science moving through successive stages up to the inclusion of knowledge in commercial applications. Equally, it is building on the approach of the second generation which recognized the complexity of innovation systems (national, regional, local, sectoral), with many feedback loops between the different stages. In the approach of this third generation, innovation is not considered as a linear process that starts with research, eventually leading to development, translated later into growth in the territories that have more capabilities. Instead, it is the product of a policy mix, including several bodies and stakeholders in which the territories, their specificities and conditions are paramount.

Notwithstanding the general idea that a territorial approach is required for the study of innovation and knowledge creation, at the normative level the main policy action is summarized in the Agenda 2020 that calls for the achievement of 3 per cent of the EU's GDP (public and private) to be invested in R&D, in order to achieve smart growth.

The aim of the present chapter is to analyse the role played by science-based activities in generating a knowledge economy, and in increasing innovation capacities of European regions.² The chapter first presents the spatial trends of the ‘knowledge economy’ in Europe (section 3), measured on the basis of a definition of ‘knowledge economy’ (section 2). When associated to the spatial innovation adoption patterns (section 4), these trends show a striking discrepancy between knowledge and innovation at the regional level and witness that R&D (and formal knowledge in general) does not necessarily equal innovation. This main result allows to claim that the pathways towards innovation and modernization are differentiated among regions according to local specificities (section 5). From this statement, thematically focused innovation policies are suggested (section 6).

2 A multidimensional definition of the knowledge economy

Much research has been produced since the 1980s on the idea of a knowledge-based economy, and on the preconditions for knowledge creation. However, when we look carefully into the existing literature, two striking aspects emerge. On the one hand, it appears evident that the knowledge-based economy does not have a unique interpretative paradigm, but has been (and still can be) defined on the basis of different approaches ranging from the earliest sectoral, through a more recent functional to the latest relation-based approach. As a consequence, the term is still vague and not precisely defined, and thus rather different policy suggestions have been highlighted. On the other hand, it appears quite evident that the different approaches to the concept share one common element, that of the central role played by spatial elements in the creation and diffusion of knowledge, both evidenced by empirical analyses or deductively derived from theoretical elements.

Although early use of the term goes back to the work of Fritz Machlup (Machlup, 1962), only in recent years has the concept of the knowledge-based economy begun to spread in the scientific and political literature. This is mainly due to work sponsored by the OECD (David and Foray 1995; Foray and Lundvall 1996). The European Union set itself the goal in 2000 of becoming the most competitive and dynamic knowledge-based economy in the world. It subsequently confirmed that goal in 2005, submitting its Structural Fund resources to achieve it.

But what does this concept really mean? Vaguely, we know that research, human capital, creative utilization of scientific concepts and information should merge, giving rise to continuing innovation and advanced production. The OECD suggested using about sixty indicators – among which R&D and high technology activities play a dominant role – to measure the knowledge-based economy (OECD 2004; Van Oort and Raspe 2006).

If we want to adopt a historical approach to the interpretation of the concept, sector-based definitions and function-based definitions were successively proposed and held for long periods. While human capital has always been considered as a basic condition for any knowledge-based development, different factors were indicated as the driving forces of change. In an early stage, which can be located in the late 1970s and the 1980s, most attention was directed to ‘science-based’ (Pavitt 1984) or high-technology sectors; regions hosting these sectors were considered as ‘advanced’ regions leading the transformation of the economy. New jobs were expected mainly from these new sectors, while more traditional sectors were expected to restructure or even to relocate abroad, giving rise to serious tensions in the local labour markets.

It soon became evident that this dichotomy was too simplistic, and that many knowledge-based advances were possible and were actually introduced by ‘traditional’ sectors – such as textiles and car production – in their path towards rejuvenation. Furthermore, the growing complexity of technological filière inside the value chain increasingly underlined the relevance of advanced tertiary sectors. These supplied producer services mainly in the form of consultancy for process innovation (proper acquisition and use of advanced technologies, tailor-made software, systems integration in production, administration and logistic processes, organizational support) and for product innovation (marketing, design, testing, advertising, finance, distribution).

In the second stage, which developed mainly during the 1980s and 1990s, a function-based approach was preferred (even though it overlapped conceptually with the previous one), which stressed the importance of pervasive and horizontal functions such as R&D and higher education. ‘Scientific’ regions, hosting large and well-known scientific institutions, were studied deeply and relationships between these institutions and the industrial fabric were analysed, with some disappointment as far as an expected but not often visible direct linkage was concerned (MacDonald 1987; Monk et al. 1988; Massey et al. 1992; Storey and Tether 1998). Indicators of R&D inputs (e.g. public and private research investment and personnel) and, increasingly, indicators of R&D output (e.g. patenting activities) were used in order to understand the engagement of firms and territories on knowledge, intended as a necessary long-term precondition for continuing innovation (Dasgupta and Stiglitz 1980; Antonelli 1989; Griliches 1990). This approach, equating knowledge and scientific research, was the one re-launched by the European strategy defined in the Lisbon Agenda.

It is difficult to escape the impression that both the sector-based and the function-based approaches to the knowledge-based economy, both driven by the need to measure and quantify, result in a simplified picture of the complex nature of knowledge creation and its relation to inventive and innovative capability. The presence of advanced sectors and advanced functions such as R&D and higher education are special features of only some of the possible innovation paths and, though relevant, cannot be considered as necessary or sufficient preconditions for innovation. Furthermore, emphasizing the stock of human capital, advanced functions and sectors may risk overlooking the interactive process between the different actors of knowledge development, which is increasingly seen as the crucial element in knowledge creation and evolution. This element is typical of production contexts characterized by the presence of SMEs but also of the contexts where big firms develop their own internal knowledge, culture and know-how by enhancing internal interaction and boosting selective external interaction with industrial partners, schools, professionals and research centres. Therefore, a rather different approach should be utilized, a cognitive one, stressing the relational, cultural and psychological elements that define the preconditions for knowledge creation, development, transmission and diffusion.

The third stage of reflection, typical of the present day in which a relation-based approach is preferred, concentrates on the identification of a ‘cognitive capability’ (Foray 2000): the ability to manage information in order to identify and solve problems, or, more precisely in the economic sphere, the ability to transform information and inventions into innovation and productivity increases, through cooperative or market interaction. The ‘learning’ region is identified as the place where such cognitive processes play a crucial role, combining existing but dispersed know-how, interpretation of market needs, information flows with intellectual artefacts such as theories and models and allowing the exchange of experiences and cooperation (Lundvall and Johnson,1994). Especially in contexts characterized by a plurality of agents – such as cities or industrial districts knowledge evolution ‘is not the result of individual efforts in R&D within individual firms, but rather the combination of complementary capacities and of widespread interactive learning processes, which involve many “customers” and “suppliers” along a well-defined filière or supply chain’ (Cappellin 2003: 307).

What is striking in all the approaches mentioned above is the central role played by spatial elements in creating new knowledge and in supporting inter-regional flows of knowledge, both evidenced by empirical analyses or deductively derived from theoretical elements. Each approach defines a type of innovative region (Table 1.2): with a sector-based approach, technologically advanced regions are highlighted; with a functional approach, scientific regions are evidenced; and with the relational approach, innovative networking regions are analysed.

Table 1.2. Complementary approaches to the knowledge economy

Sector-based definitions (1970-80)

Function-based definitions (1980-90)

Relation-based definitio...

Table of contents

• Cover Page
• Half Title page
• Series page
• Title Page
• Copyright Page
• Contents
• List of figures
• List of maps
• List of tables
• List of contributors
• Preface
• Introduction: cities, regions and universities as knowledge and innovation creators
• Part I Universities: local/regional institutions of knowledge creation and innovation in national and international contexts
• Part II Universities, entrepreneurship and innovation-driven development?
• Part III Academic footstep in the city
• Index