As described earlier, the emergence of the knowledge-based economy around the world has been widely acknowledged at an international level, (OECD 1996 and Work Foundation 2006), and also increasingly so at national (DTI 2003 and Shapira et al. 2005) and regional levels. This has led to many countries large and small developing strategies to harness the opportunities of the Knowledge Economy, including nations as diverse as the US, UK (DTI 2004), New Zealand, Malaysia and Scotland (Scot Exec 2001).

Knowledge creation is a key driver of the Knowledge Economy and the United States is the world leader in this regard investing the most into the creation of knowledge; some $285bn annually. This compares with other leading nations as shown in Table 1 (OECD 2005).

EU and UK

Developing the world’s strongest Knowledge-based economy has become a key goal for the European Union as launched at the Lisbon 2000 Council (Lisbon 2000 EU Council Strategy).

“…to become the most dynamic and competitive knowledge based economy in the world”

At a European level the disparities in economic performance between regions, even within countries, are highlighted by Figures compiled by the European Commission (EUROSTAT 2004) and shown in Figure 1. The United Kingdom provides the most striking example of this with Inner London generating GDP per capita at 288% of the EU average while at the other end of UK performance are the Isles of Scilly registering 65% (Wales Objective One region – 73%).

Figure 1: GDP per capita 2001, NUTS 2 level in % of EU-25 average (EU-25 = 100).

The leading regions are typically those including the capital city and this performance aligns with the intensity of knowledge-based activity as has been shown in Cooke and Clifton (2005). However, this measure serves to highlight one of the limitations of simple GDP measures. As ‘output’ location is recorded rather than ‘income’ region the apparent prosperity of regions can be misleading. For example, relatively few people live in Central London, though a huge amount of GDP is generated. Much of the wealth created in the capital flows out in pay packets to be spent in the commuter-belt. Wales experiences the same phenomenon, with workers flowing into the capital, many from the relatively poor Valleys, to create GDP that registers as an output of Cardiff.

Much of the Community level action focuses on issues such as reform of state aid, removal of obstacles to physical, labour and academic mobility and completion of an agreement in the ongoing World Trade Organisation negotiations. However, as described in Chapter 2, this follows through down to the national and regional levels, including strategy for Structural Funds interventions.

Considering the intentions of the European Union, how does it currently perform in terms of the knowledge-based economy? Statistics compiled by EUROSTAT show that over 40% of EU employment is in knowledge-based industries with about half of this in manufacturing and market services (i.e., not Health or Education), as shown in Table 2.

Table 2: EU Knowledge Based Employment – 2005, Work Foundation (2006).

Sector	% of total employment
Tech based manufacturing	6.9%
- High-tech manufacturing	1.1%
- Medium tech manufacturing	5.8%
Market Services	15.3%
- High tech services	3.5%
- Financial services	3.2%
- Business / Communications	8.6%
Health, Education, Cultural	19.4%
Total	41.5%

The importance of the Knowledge Economy is continually growing in the UK. Current trends would see manufacturing and agriculture account for only 15% of UK output by the end of the decade as the service sector continues to grow (Leadbeater 1999). These trends are reflected in the growth of employment in knowledge-based industries since the mid-80s shown in Figure 2.

Figure 2: UK Employment in knowledge based (solid line) and other (dashed line) industries, from Coates and Warwick (1999).

However, this overall growth of the Knowledge Economy sits above a wide variance in performance amongst UK regions that is acknowledged by both Government (Edmonds 2000 and DTI 2001) and academic observers (Hughes 1999, Cooke 2002, Clement 2004 and K Group 2006).

Over recent years there has been a restructuring of the Welsh economy in the face of global challenges that have squeezed traditional sectors, in particular manufacturing. In this regard, the Welsh Assembly Government is trying to support the development of the knowledge-based economy. This ambition, reflecting the pillars of the knowledge economy is captured in the Wales Spatial Plan (WAG 2004c):

“We need an innovative, high value economy for Wales which utilises and develops the skills and knowledge of our people: an economy which both creates wealth and allows that prosperity to be spread throughout Wales: an economy which adds to the quality of people’s lives as well as their living and working environments.”

Great differences in prosperity can be noted within the regions of Wales (Morgan 2001). This is demonstrated by Figure 3 presenting the disparity between East Wales, and West Wales and the Valleys (K GROUP 2006).

Figure 3: GVA by South Wales region compared to UK average – 2003 from Knowledge Economy Theme: Interim Report (Stats Wales Welsh Assembly Government 2006).

Wales Spatial Plan, Swansea Bay, Waterfront and Western Valleys Using a definition developed from the OECD sectoral description of the knowledge economy (OECD 1996), De Laurentis and Cooke (2003) present the regions of West Wales and the Valleys against other key European regions (in Table 3).

This suggests that both ‘East Wales’ and the ‘West Wales and Valleys’ regions ‘qualify’ as regions with a knowledge-based economy, meaning that there is an existing knowledge-economy to be supported and developed.

‘West Wales and Valleys’ includes the Wales Spatial Plan region of Swansea Bay, Waterfront and Western Valleys, which is developing its own Knowledge Economy strategy as part of the Spatial Planning process. The neighbouring region of ‘East Wales’ is also developing a strategy for development of the Knowledge Economy using the services of an external commercial consultancy (Local Futures 2006).

The research and strategy development of the South West Wales effort is being driven by the Knowledge Economy Research Group at Swansea University. This work has focused on identifying regional challenges, relating to human capital, innovation and infrastructure, and developing recommendations and actions through use of regional and international experts (K-Group 2006 and Davies et al. 2007).

This approach to developing ‘regional’ knowledge economy strategies has been adopted in the United States, Europe and the UK (Boddy 2005).

While the term ‘cluster’ has been increasingly used over recent years, the concept has been apparent for centuries and acknowledged for some time, though perhaps subject to different terminology. Rocha (2004) for example charts how academics have studied the phenomenon since the ‘Industrial Districts’ described by Marshall in the 1890s, all the way through to Porter (1990) at the end of the last millennium. Rocha’s work cites early examples of silk traders in China, along with the coming together of suppliers and manufacturers during the industrial revolution, together with their contemporary equivalents, such as the software companies of India or the call centres of Sydney.

These groupings of companies suggest that much of the competitive advantage enjoyed by their members lies outside the firm (Porter 2000), such that the ‘the whole is greater than the sum of the parts’. Porter describes how ‘clustering’ can help the productivity of both firms and regions in a number of ways:

Elsewhere Porter and Stern (1999) provide a formal definition of the concept (which is also used by the DTI (2001);

‘Clusters are geographically proximate groups of interconnected companies, industries, and associated institutions in a particular field, linked by commonalities and complementarities.

As the definition suggests a cluster does not include solely competing firms, but is a much broader phenomenon, which “extend(s)downstream to channels or customers and laterally to manufacturers of complementary product (and services) or companies related by skills, technologies or common inputs” (Porter 2000). This encompasses the roles of other stakeholders within clusters including universities, trade associations and government.

Porter and Stern (1998) also point out that not all actors within a cluster are necessarily aligned with a particular industry, though rather they come together to support each other’s innovative activity. However, when considering a cluster it should be done with regard to the sector under investigation as aggregation to the level of industry or broad groupings such as ‘manufacturing’ or ‘high-technology’ lose the meaning of the connections and interrelationships.

Clusters exist in all manner of industries, though are of particular interest in knowledge-driven sectors because of the importance of localised skills and tacit knowledge spillovers. Clusters differ from networks in that they do not rely on any formal or informal organisation of actors such as chambers of commerce, industrial fora etc. (EU 2003).Furthermore, clusters are not necessarily dominated by large companies: an EC study (EU 2003) shows that they typically involve a mix of small and large firms, as shown in Figure 4.

Figure 4: Dominating firm size of clusters included in European Commission study (EU 2003).

Clusters historically often developed around a natural resource, such as mineral deposits or a natural harbour, or a large market, such as towns or cities (Figure 5). This last influence is still reflected in the European Commission study of European clusters, which shows most exist in urban settings (EU 2003);

Figure 5: Geographic location of clusters included in European Commission study (EU 2003).

Many clusters have developed around the availability of knowledge in the region and this is evermore important in the modern Knowledge Economy sectors. This leads to co-location of firms, the spin-off and start-up of new related firms and the development of other businesses to support their activities, and the growth of a cluster. The nature of such firms is not just competitive and often occurs with overlap between sectors (e.g., venture capitalists, patent attorneys, recruitment agencies, accountancy firms etc.). The interrelationships that give rise to this are presented in Porter’s ‘Diamond’ Model shown in Figure 6.

Figure 6: Porter’s ‘Diamond’ Model for Competitive Advantage of Nations (Porter 1990).

Clusters of businesses related to a specific sector not only draw upon the common innovation infrastructure (or innovation system as discussed later), but also add to it, creating a self-reinforcing virtuous circle (Porter and Stern 1999). This effect is also demonstrated by the work of Varga (2000), who notes, however, that a critical mass of agglomeration within the region is needed for this to occur.

The study conducted by the European Commission also investigated the interaction and types of networking between businesses in the clusters examined. As shown in Figure 7 most of the clusters investigated had extensive informal networking and collaborative R&D activity;

Figure 7: Networking between firms in clusters: European Commission study (EU 2003).

The virtuous circle can lead to growth that is then compounded by the establishment of reputation, further attracting skills, investment and opportunities to the region. Examples of this include ‘Silicon Valley’ (Bresnehan et al. 2001, 2007) and ‘Route 128’ (Dorfman 1983), along with Silicon Glen (Turok 1993) and Cambridge Biotechnology clusters in the UK (Keeble and Tomlinson 1999 and Todtling and Trippl 2005).

As described earlier the effects of clusters do not solely relate to existing firms therein, but also to the formation of new enterprise. The availability of new opportunities within a cluster helps promote entrepreneurship and the presence of support organisations, potential customers and suppliers’ acts to facilitate innovation and entrepreneurship (Rocha 2004). The presence of local networks can also help decrease cost and uncertainty in the development of start-ups, aided by flow of knowledge (Almeida and Kogut 1997).

Clusters also represent a foundation for the formation of formal and informal knowledge distribution networks that support innovation (OECD 1996), which ties in with the concept of knowledge spillovers discussed earlier. The information and knowledge exchange within clusters is the key driver in their development in what Keeble and Wilkinson term an ‘innovative milieu’ (Keeble and Tomlinson 1999) as part of ‘regional collective learning’. This concept describes the development of a collective regional knowledge base caused through interactions such as networking, research collaborations and the movement of personnel between companies and other organisations.

Proximity is a key component in successful clusters (OECD 1996 and Porter 2000), particularly in regard to facilitating knowledge-spillovers (EU 2003), described as:

“The proximity of customers, competitors, suppliers, universities and research institutions provided impetus (for) the creation and exchange of information and increases opportunities for innovation.”

Maskell and Malmberg (1999) outline how the competitiveness of a firm, particularly in the long-term, depends upon its ability to continuously upgrade its knowledge base. To achieve this it must find knowledge sources that provide competitive advantage. As tacit knowledge is the least transferable it requires that businesses place themselves close to its source. Additionally, cost is a factor in developing and maintaining a company’s knowledge base, making proximity to knowledge sources a cost-effective way of closer and more frequent personal contacts.

While proximity to sources of knowledge and other linkages are important elements of clusters, it must not be forgotten that high-technology companies generally exist in national and international networks, serving global markets (Keeble and Tomlinson 1999; Muller, 2007).

On a global scale the DTI report ‘UK Competitiveness: Moving to the Next Stage’, (Porter and Ketels 2003), presents the UK as a whole as figuring in a number of significant clusters including services, defence, telecommunications, health care, entertainment. Further sectors such as biotechnology and motor sport are also noted to be of particular significance.

Wales as recorded in documents such as the Wales Spatial Plan already acknowledge a number of sector clusters including electronics, biotechnology, automotive and aerospace. These have been identified in the DTI study of UK clusters (DTI 2001). Each of these represents a significant employment and numbers of businesses (Table 4).

While not all of the employment may refer to higher skilled employment or ‘knowledge workers’ the sectors involved fall within sectoral definitions of the knowledge economy (OECD 1996) and present the importance of the knowledge economy employment within the region.

An observation in the DTI assessment of clusters (DTI 2001) in Wales; is that while there exists significant specialisation with a number of clusters, they are generally and often weakly embedded and dependent upon foreign owners and markets or industries across the border in England. This reflects the concerns regarding the ‘embeddedness’ of businesses in the region and the focus given to developing indigenous enterprise within sectors and clusters (Cooke and Clifton 2005).

Clusters are generally built up spontaneously (EU 2003). However, the question remains as to whether it is possible to develop them in cities and regions and how it could be achieved. The conclusion put forward by governmental organisations (EU 2003), academics (Cooke 2002, Porter 2000) and other bodies is that it is possible, subject to the availability of key components including leadership and vision (Porter 1990, Cooke 2002).

This is in keeping with the model proposed by Porter (1990, 2000), where government can affect aspects including factor conditions, firm strategy, and rivalry and demand conditions. Examples of each of these include provision of training or new knowledge (e.g., funding training schemes or funding academic research), competition policy (regulation/deregulation of industries) and changing consumer behaviour (e.g., environmental legislation), as shown in Figure 8 (Porter 2000). It is also suggested that because of the importance of proximity regional administrations are best placed to assist cluster development (EU 2003).

Figure 8: Aspects of Economic Policy in Cluster Development (Porter 2000).

Wales entered the new millennium equipped with a new Assembly to fulfil its ambitions, but much like its devolved neighbours of Northern Ireland and Scotland was about to attempt this in the face of economic decline, poor conditions for entrepreneurship and the disinvestment caused by globalisation (Cooke and Clifton 2005).

The scale of this challenge is highlighted by the fact that Wales, with 5 percent of the UK population, only contributes 4.5 percent of total economically active persons and 3.9 percent of GDP in the UK. The Welsh Assembly Government has set itself the target of closing the gap with the rest of the UK economy by raising per capita GDP to 90% of UK levels within a generation (WAG 2001). This target is an enormous aspiration that would require national economic performance to be raised to a level not seen in a century. This is shown in Figure 11 presented Crafts recently to a conference in Cardiff.

Figure 11: GDP/Person in Wales as % of Great Britain GDP, selected years (Crafts 2005).

The pressure on manufacturing and basic industries continued with the closure or relocation out of Wales of many inward investors and the termination of steel production at Llanwern. In the period between 1998 and 2003 Wales as a whole lost 57,000 manufacturing jobs. This has again raised the question of how ‘embedded’ multinationals are (or were) in the Welsh economy, with the suggestion that the presence of functions beyond assembly such as research and development would improve embeddedness (Phelps et al. 2003).

In addition to the continued pressure on manufacturing, the supply of FDI opportunities available was starting to fall during the end of the 1990s due to a slow-down in the global economy (Young et al. 1994) and the emergence of new attractions for FDI, most notably in China and India (Chen 1996). Despite the emergence of these low cost competitors it is observed that wage rate versus skills level remains an issue, working in favour of the relatively better skilled workforces of developed nations (Wei et al. 1999). Furthermore another factor which also hampers future growth for the region is an aging population, which though not a unique regional challenge, does feature worse than for the country as a whole (EU 2005).

These challenges meant the problems of the new millennium would not be fixed by the same solution of solely attracting foreign investment by cheap labour and access to markets used at the end of the last century.

Rationale

At the end of the twentieth Century much of the Welsh economy was significantly trailing behind, such that GDP was only 73% of the European average (WEFO 2004) meaning that parts Wales qualified for ‘Objective One’ assistance (Figure 12). This level of assistance represented the highest level of aid provided by the EU and was targeted at regions with GDP below 75% of the EU average (Figure 13).

Figure 12: Objective One Areas in Wales (EU 2004).

Figure 13: Objective One Areas in the EU (EU 2004a).

The fact that not all of Wales qualifies for such assistance reflects the variation in prosperity across the country. This is highlighted by the fact that disposable incomes in the Vale of Glamorgan are as high as those in the more affluent parts of Bath and Bristol across the bridge, while the mining communities of the Valleys just a few miles from the other side of the M4 remain as impoverished as the most deprived parts of Inner London (Lovering 1999).

The reasons for this poor relative performance were structural dependence upon low value added activities, low productivity in certain sectors and high levels of unemployment within an overall low level of economic participation. Objective One funding came about thanks to the creation of a new statistical region ‘West Wales and the Valleys’ that presented and highlighted the economic woes of this part of Wales (Cameron et al. 2002). The value of this assistance totalled some £1.2bn in grant aid – to be match funded from other sources.

While much effort has been made to address the economic weaknesses of much of Wales, including through use of European Objective 1 funding, the performance of parts of the Welsh economy remains significantly behind that of Europe as a whole. This is highlighted by the fact that much of Wales still qualifies for the highest level of assistance from the EU, now termed ‘Convergence Funding’.

As previously described in this section WAG outlines its strategy for economic development in ‘Wales: A Vibrant Economy’ (WAG 2005b). This strategy builds upon the vision of integrating national and regional policy with the vision of the European Union and the ‘Lisbon Agenda’ of social and economic regeneration. To achieve this Wales has the support of Convergence Funding worth £1.3bn for the West Wales and Valleys region while other areas of Wales qualify for support worth around £120m from the ‘Competitiveness Fund’, which was previously called Objectives 2 and 3. Most of the funding available (65%) is set for ‘Lisbon related investments’ (WEFO 2006) and has been earmarked in line with 9 European Regional Development Fund (ERDF) and European Social Fund (ESF) priorities (WEFO 2006);

ERDF

• Building the knowledge based economy.
• Improving business competitiveness.
• Developing strategic infrastructure.
• Creating an attractive business environment.
• Building sustainable communities.

ESF

• Supplying young people with the skills needed for employment
• Increasing employment and tackling economic inactivity
• Improving skill levels and improving the adaptability of the workforce
• Making the connections – modernising our public services

While much effort has been made to address the economic weaknesses of much of Wales, including through use of European Objective 1 funding, the performance of parts of the Welsh economy remains significantly behind that of Europe as a whole. This is highlighted by the fact that much of Wales still qualifies for the highest level of assistance from the EU, now termed ‘Convergence Funding’.

With the close of “Objective 1” funding in 2006, the West and the Valleys region of Wales were awarded the highest level of support from the European Union for the Structural Funds programming round 2007–2013 (Convergence).

Convergence, the successor to the Objective 1 programme 2000-2006, covers 15 local authority areas in the West Wales and the Valleys region (Figure 14).

Figure 14: Convergence Region of Wales.

The Convergence programmes for West Wales and the Valleys comprises of funding from two separate European Structural Funds: the European Regional Development Fund (ERDF) and the European Social Fund (ESF). Around £1 billion of ERDF funds has been allocated to help progress the region’s transformation into a sustainable and competitive economy by investing in the knowledge economy and helping new and existing businesses to grow.  It is focused on regenerating Wales’ most deprived communities, tackling climate change and improving transport. Over £690 million from the ESF has been slotted to be used to tackle economic inactivity, increase skills and employment. The aim is that together, with match funding, Convergence will drive a total investment of £3.5 billion in West Wales and the Valleys (WEFO 2009).