Concluding comments - Support of research in sciences underlying product areas to gain informat

S: Support of research in sciences underlying product areas to gain information directly and by monitoring

2.7 Concluding comments

Within a post-industrial and service-based economy such as Britain, the challenge for enterprises is no longer just to obtain competitiveness through price-induced demand, as this is not sustainable, but to generate continual entrepreneurial (Schumpeterian) profits via differentiation and enhanced value-added knowledge. Economic growth is first of all a process of transformation, not of convergence to a steady-state growth path. As a result, the ability to generate and carry out technical change is not only a key determinant of how

adaptable enterprises or economies are, but also a key basis for comparative advantage (Drucker, 1998a). The relevance of knowledge and technical change in relation to enterprise, industry, regional and national competitiveness has been extensively commented upon in the last decade; in particular the application of ‘new’ growth theory has been used to emphasise increasing returns. Questions however remain regarding whether or to what extent advanced economies have undergone transition to a ‘knowledge’ based or driven economy and the evidence to support this perspective. In addition the assumption that knowledge creates wealth could also be regarded as being oversimplified as this does not take into account the influence of other factors related to growth. While ‘new’ growth theory has highlighted knowledge as an economic variable it cannot fully incorporate the diversity of variables involved in the growth process, nor can it fully incorporate the differentiated nature of knowledge in order to model the process of growth. Thus, in a fundamental way it does not advance what has already been known via the work of Abramovitz (1956) regarding knowledge and the process of technical change.

Although tacit knowledge has been stressed as being important for competitiveness, it is crucial to understand that it is not an isolated process, but must be seen in relation to creative and entrepreneurial elements. Knowledge alone is not a determinant of technical change, for factors such as intuition or contextual circumstance play a significant role. Individual and group creativity, entrepreneurial characteristics, organisational or market contexts are important determinants of competitiveness and technical change. Further, whilst much is made of the need for constant technical change within the modern hyper-competitive environment, this perspective commonly ignores the fact that enterprises, or more specifically their owners or managers, commonly seek to have an easier life by resisting the need for technical change (Drucker, 1998a; Sundbo, 1998). The process of technical change encompasses risk, and encouragement to take risks is often increased when there is a slump in sales or enterprise survival is threatened; in such circumstance the need for technical change becomes more urgent.

Quantifying knowledge (particularly that which is tacit) as a process that underpins growth still remains a problem, nonetheless it can be assumed that firms engaged in APS act as key gatekeepers, suppliers and carriers of knowledge for clients and regions through their intermediate role of providing technical change related options.55 There are two principal ways by which they do this. At a basic level this includes the dissemination or transfer of either or both codified and tacit knowledge from elsewhere, and combining this with client specific requirements; the other option includes the creation of new knowledge, for example through research and development (R&D). In both circumstances, the role of APS firms is to relieve their clients of the need to acquire and deploy knowledge, which they may not have any expertise in, or involvement with. APS firms not only play a major role in the transfer process between economic agents (by means of repeated interaction), but can also develop links between tacit knowledge buried within routines associated with firms, and codified knowledge contained in the outside world (Lawson and Lorenz, 1999). In this regard, APS firms can play a key role in stimulating technical change and competitiveness through the application of creatively combined knowledge (Rubalcaba-Bermejo, 1999; Wood, 2002b).

The evolution of APS within most economies has been built not only upon the functions of other industries, but also the establishment of new forms of economic activity both nationally and internationally. The APS sector nonetheless presents a critical problem in relation to economic analysis, in that not only are output and impact difficult to identify, but also their key product (i.e. creative knowledge) is often invisible and vastly differentiated and contextual. Because enterprises involved in APS are not homogenous, they utilise different types of knowledge and adopt different approaches to learning, this contributes towards differences in the relative weight attached to tacit and codified knowledge and the ways in which technical change is pursued or realised. As a result, firms or the sector cannot be examined in isolation but require a layered appreciation of enterprise characteristics, market relationships and wider socio-economic influences for a contextual understanding of function, operation and trade. Regional and national bodies therefore need to focus not only on the development or evolution of knowledge, but also on the dynamics surrounding the circumstances within which firms involved in APS learn and interact.

Notes

This view followed the path set by the Physiocrats, a school of French economists exemplified by the likes of François Quesnay (1694–1774) and Anne-Robert-Jacques Turgot (1727–1781). They contributed to popularising the terms ‘laissez faire’ and ‘laissez passer’. Their free market approach was linked to the idea that natural law would guide economies without intervention. They also held that agriculture and mining were the only productive forms of economic activity, a view that was perhaps natural given that the Industrial Revolution had yet to occur.

Riddle (1986, p.44) for instance cites Katouzian (1970) as one of the first to suggest that comparative advantage operates in the service sector along the same lines as that associated with physical goods. Katouzian for instance, pointed out that England had enjoyed a comparative advantage in shipping and finance, income from such activities helped to progress economic development.

The identification of such sectors is referred to in Marshall (1890, p.109), where the ‘division of goods into successive orders’ is attributed to Carl Menger (founder of the Austrian school of economics), in Grundsdtze der Volkswirthschaftslehre (translated as Principles of Economics) published in 1871. In this work, Menger identified subjective valuation in light of human behavioural needs as the driving force of economics, and not cost-value as associated with the classical school of thought. Fisher followed in this framework by referring to these sectors as ‘successive orders’; the first encompasses the production and distribution of goods vital for life; the second is linked to semi-essential products; the third incorporates services and intangible activities that are regarded as luxuries).

Reference within early literature often cited Engel’s law, where stabilised demand for manufactured products gives way to services (Clark, 1940). Back in 1857, the German economist Ernst Engel observed that in contrast to the poor, families that grew richer would allocate smaller portions of their household budget to foodstuff and would direct their expenditure towards more luxury goods. He concluded that people with different income levels have different spending patterns, and that changes in economic variables such as income, savings rate, interest rates and borrowing behaviour are likely to impact on the marketplace.

Productivity is typically measured as output per unit of labour, a criterion that works against many services such as banking, marketing or design.

Rowthorn and Ramaswamy (1998, p.13) state that deindustrialisation is a natural consequence of future growth in advanced economies; such nations should not be alarmed unless there are inherent structural problems.

This difference, however, is not reflected, or at least not to the same extent, in wage and salary demands, which in the long run have broadly kept in line with manufacturing. The diversity of services is further reflected in the character of the labour force, which as in manufacturing ranges from relatively low-skilled metal bashers to highly skilled specialists; this difference impacts upon income, employment supply and demand dynamics (Office for National Statistics, 2000, Chapter 5).

See company web sites referring to their activities and accounts at: www.ge.com and www.ibm.com

Fordism is a form of production technique implemented by the Ford Motor Company in the 1920s, it is also based upon the work of Frederic Taylor as outlined in his book ‘Scientific Management’ published in 1911.

Negatively however in relation to the UK, productivity has been below par in context with other advanced economies, research by the National Institute of Economic and Social Research shows that manufacturing productivity is 55 per cent higher in the US than in the UK, 32 per cent higher in France and 29 per cent higher in Germany (ibid., p.6). The UK has also other structural problems; UK manufacturers on average invest less than their competitors in capital equipment. With some exceptions, there is less expenditure upon research and development and greater rates of failure of turning good ideas into commercial success, whilst at the same time the rate of new or improved product introduction is lower than other leading European Union competitors. The UK also suffers from low technical and manufacturing related skill levels compared to its western European competitors (DTI, 2002, p.15).

In fact it is: 'incorrect to assume that for an industrialised country to obtain solid performances it has to give up traditional sectors (the standardised sectors) where demand is declining, and to re-deploy resources in high growth sectors. Such a choice can lead to a deterioration of industrial competitiveness if a massive relocation of the traditional sectors … is not followed by a quick re-deployment of the resources made available' (European Commission, 1999b, p.68).

Mainstream growth theory failed to differentiate between capital and consumption goods, since the 'model economy produces only one composite commodity, which it can either consume currently or accumulate as a stock of capital' (Solow, 1956, p.9). This focus can be explained by the desire of growth theory to analyse business cycles rather than the growth process itself.

Both Solow (1956) and Swan (1956) developed similar models, but neither knew of each other’s work. Their models were developed in response to the neo-Keynesian Harrod (1939) / Domar (1946) model, which assumed that there was a constant return to scale in relation to technical change, and that the production function was the same in all countries and was an exogenous public good. The Solow-Swan concept is akin to a growth accounting model. It assumes that because capital is based on known

technology and because technology is improving, new capital is more valuable than that which is old, and thus growth rates of economies depend on the investment rate, and the rate at which capital is converted into output.

Traditional growth theory also relies on a mathematical treatment of capital (it appears in economic models as a numerical variable in the production function).

If exogenous technical change were disregarded, higher productivity could be achieved only by increasing capital per worker; this in the long run would cause the marginal productivity of capital to decline substantially. Ultimately, the marginal productivity of capital would approach levels where growth ceased, as resources were exhausted.

In the neo-classical approach, it is assumed that growth (real GDP increase) is linked to technical change via increased levels of saving and investment. Technical change advances productivity as well as new profit opportunities, which consequently influence investment and savings that help to increase prosperity and growth. These latter effects, however, do not influence the pace of technical change; it is assumed that this is related to chance.

Neo-classical theory assumes that capital is unchanging except in quantity; this simplification obscures understanding of economic reality in the context of technical change, where the characteristics of goods often change over time. Further, it is meaningless to make generalisations about the marginal productivity of capital, when output cannot be evaluated in relation to expanding or declining industries.

Romer (1986, p.1003) suggests that 'per capita output can grow without bound possibly at a rate that is monotonically increasing over time. The rate of investment and the rate of return on capital may increase rather than decrease with increases in the capital stock'. This economy-wide effect of capital accumulation outweighs the eventual limiting consequence of increasing capital per worker within a given firm. Therefore, overall, marginal productivity does not decline with increasing Gross Domestic Product (GDP) per capita as within the neo-classical approach. This also explains why convergence of economic performance amongst countries or regions (as advanced by the neo-classical model) does not take place, since growth over time does not level out but rather exaggerates differences.

Proponents of ‘new’ growth theory such as Romer and Lucas have followed the preliminary route set by Arrow (1962) and Kaldor (1957) by linking new investment in human capital with technical progress in the form of learning, giving rise to endogenous growth theory.

Further, whilst Romer focuses upon technical change, he deals only with additional new kinds of goods; knowledge still continues to be embodied in capital goods.

There are inherent links between ‘information’ and ‘knowledge’, but they are not the same; rather they are two distinctive and interlinked concepts. Information is made up of data that are capable of yielding

knowledge, whilst knowledge is developed from accumulated information plus acquired skills and creativity. In this regard, to be knowledgeable implies that recipients need key capabilities or competencies that are relevant and applicable.

Types of learning include: by doing (Arrow, 1962), by using (Rosenberg, 1982), by hiring (Huber, 1991), by searching (Bell, 1984), learning by learning (Stiglitz, 1987), by trying (Fleck, 1994), by interacting (Lundvall, 1988), by selling (Thomson, 1989), from inter-industry spillover (Malerba, 1992), by borrowing (David, 1993), by failing (Bahrami and Evans, 1995).

It is therefore not surprising that economic historians amongst others have focused on the movement of people (from regions or nations) as key mechanisms of knowledge transfer.

Tsoukas (1996, p.14), for example, suggests that tacit and explicit knowledge are mutually co- dependent and should not be viewed as separate variables, further the author suggests that tacit knowledge is not explicit knowledge internalised. Additionally to attempt to divide the two as Nonaka and Takeuchi (1995) do is to ‘miss the point’.

The term 'spillover' refers to the position where some particular knowledge or idea, which perhaps is the result of the development efforts of a person, organisation or group, becomes freely available to all. Spillovers are likely to lead to increased competition, which consequently reduces profits for the innovating firm and boosts the profits of imitators. Many studies including that associated with Marhsall (1890) have suggested that geographical proximity increase the probability of knowledge spillover occurring between firms.

Whilst instruments such as trade secrets, patents and copyright provide creators with some limited protection, knowledge can over time be duplicated, purchased off-the-shelf or learned, thus eroding advantage derived by the originators.

For a more in-depth critique of ‘knowledge management’ see Spiegler (2000).

The economic and social transformations included: 'a) the shift from a manufacturing … to a service- based economy, providing primarily human services; b) a change in the character of social stratification, based upon the emergence of a new professional technical elite; c) critical importance of technical knowledge, harnessed and controlled for use by the state in science-based industries' (Bell, 1973, p.487).

Whilst Bell focused upon aspects relating to the ‘knowledge’-based post-industrial society, he was less inclined to classify his approach as such: 'The question has been asked why I have called this speculative concept the "post-industrial" society rather than the knowledge society or the information society or the professional society … In Western society we are in the midst of a … change in which old

relations between existing power structures … are being rapidly eroded … what the new social forms will be like is not completely clear' (Bell, 1973, p.xiv).

Economic and social transformations included evolution of social stratification, a process based upon the emergence of technical elites (Bell, 1973).

Technology, for example, is a form of knowledge, although different from scientific knowledge (Layton, 1974).

A competency model is a descriptive tool that identifies the skills, knowledge, personal characteristics, and behaviours needed to effectively perform a role in the organisation and help the enterprise meet its strategic objectives

Both to various extents were interested in the process of communication via mathematical systems, information feedback, interaction, predictions and actions. In order to facilitate better communications in terms of speed and accuracy, engineers had to understand the processes and systems involved in transmitting, coding as well as reproducing data messages.

Machlup (1962, p.384).

The Kondratieff wave was somewhat overlooked after Schumpeter until the late 1970s, due to the post-war dominance of Keynesian economics (the latter sought to fine-tune the economy and eliminate inflation and recession alike). The problems of the 1970s, especially stagflation, reduced the influence of Keynesian economic and redirected focus towards the study of economic cycles. There have been numerous debates surrounding the existence of Kondratieff waves, methodological issues and the extent to which such waves influences development, this is beyond the scope of this study.

Schiller (1969) also highlighted the significance of the military establishment through government related subsidies and programmes (the development of the Internet is a classic example), in not only developing and diffusing information technologies but also in assisting American businesses to expand overseas through commercialisation and consumerism.

Castells (1996, p.231), for example, identifies the ‘post-industrial’ period of change as occurring from 1970 to 1990, when employment in services eclipsed manufacturing. Incidentally, Castells builds upon the notion of ‘informationalism’ in context of the modern economy and rise of services in developing his concept of the networked society.

The growth of ICT gross value added (GVA) was significant throughout the 1990s. GVA measures the contribution to the economy of each individual producer industry or sector in Britain and is used in the estimation of GDP. The Office for National Statistics (2003), estimates that in 2001, the contribution of ICT to UK GVA at current basic prices accounted for £63.5 billion out of a total of £880.9 billion (7.2 per cent of the total). GVA for the ICT sector grew by 109.8 per cent between 1992 and 2001, over the

same time period the entire economy grew by 61.2 per cent. The composition of growth in GVA at current basic prices generated by the ICT sector has been largely led by the service rather than manufacturing industries. The services component between 1992 and 2001 grew by 130.7 per cent (from £22.3 billion to £51.5 billion), manufacturing in contrast, between 1992 and 2001, grew by 51.2 per cent (from £7.9 billion to £12 billion), having peaked in 2000 at £13.1 billion. Due to the highly labour intensive nature of the ICT sector (as a result of the services component), 67.3 per cent (or £42.8 billion) of the factor income generated by the ICT sector in 2001 was taken-up by employee compensation, a growth of 116.9 per cent over 1992. Since 1992, the overall supply of ICT products has grown by 141.9 per cent to £199.2 billion in 2001. The UK’s domestic output of ICT products in 2001 amounted to £115.7 billion, whilst imports of goods and services, helped push the total supply of ICT products up by a further £83.4 billion. These additions are particularly significant in the supply of computers, where imports exceeded UK production. Taking the supply of ICT products in 2001 as a whole, over half was used up in UK industry via intermediate consumption, a quarter exported, an eighth invested (gross capital formation) in UK industry, mainly within the service sector, and the remainder consumed by households. Exports of ICT products meanwhile grew from £16.0 billion in 1992 to £45.0 billion in 2001, contributing 16.6 per cent of total UK exports of goods and services, and 4.5 per cent of GDP at current market prices (Office for National Statistics, 2003, p.52-60).

In evaluating productivity in relation to ICT, it is essential to distinguish contribution to economic

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