Harry Hillman Chartrand
Organization for Economic Co-Operation and Development
THE KNOWLEDGE-BASED ECONOMY
I. THE KNOWLEDGE-BASED ECONOMY:
TRENDS AND IMPLICATIONS A. Introduction B. Knowledge and economics C. Knowledge codification D. Knowledge and learning E. Knowledge networks F. Knowledge and employment G. Government policies
II. THE ROLE OF THE SCIENCE SYSTEM IN
B. Knowledge production
C. Knowledge transmission
D. Knowledge transfer
E. Government policies
III. INDICATORS FOR THE KNOWLEDGE-BASED ECONOMY
B. Measuring knowledge
C. Measuring knowledge inputs
D. Measuring knowledge stocks and flows
E. Measuring knowledge outputs
F. Measuring knowledge networks
G. Measuring knowledge and learning
The OECD economies are increasingly based on knowledge and information. Knowledge is now recognised as the driver of productivity and economic growth, leading to a new focus on the role of information, technology and learning in economic performance. The term “knowledge-based economy” stems from this fuller recognition of the place of knowledge and technology in modern OECD economies.
OECD analysis is increasingly directed to understanding the dynamics of the knowledge-based economy and its relationship to traditional economics, as reflected in “new growth theory”. The growing codification of knowledge and its transmission through communications and computer networks has led to the emerging “information society”. The need for workers to acquire a range of skills and to continuously adapt these skills underlies the “learning economy”. The importance of knowledge and technology diffusion requires better understanding of knowledge networks and “national innovation systems”. Most importantly, new issues and questions are being raised regarding the implications of the knowledge-based economy for employment and the role of governments in the development and maintenance of the knowledge base.
Identifying “best practices” for the knowledge-based economy is a focal point of OECD work in the field of science, technology and industry. This report discusses trends in the knowledge-based economy, the role of the science system and the development of knowledge-based indicators and statistics. It is excerpted from the 1996 Science, Technology and Industry Outlook, which is derestricted on the responsibility of the Secretary-General of the OECD.
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OECD science, technology and industry policies should be formulated to maximise performance and well-being in “knowledge-based economies” – economies which are directly based on the production, distribution and use of knowledge and information. This is reflected in the trend in OECD economies towards growth in high-technology investments, high-technology industries, more highly-skilled labour and associated productivity gains. Although knowledge has long been an important factor in economic growth, economists are now exploring ways to incorporate more directly knowledge and technology in their theories and models. “New growth theory” reflects the attempt to understand the role of knowledge and technology in driving productivity and economic growth. In this view, investments in research and development, education and training and new managerial work structures are key.
In addition to knowledge investments, knowledge distribution through formal and informal networks is essential to economic performance. Knowledge is increasingly being codified and transmitted through computer and communications networks in the emerging “information society”. Also required is tacit knowledge, including the skills to use and adapt codified knowledge, which underlines the importance of continuous learning by individuals and firms. In the knowledge-based economy, innovation is driven by the interaction of producers and users in the exchange of both codified and tacit knowledge; this interactive model has replaced the traditional linear model of innovation. The configuration of national innovation systems, which consist of the flows and relationships among industry, government and academia in the development of science and technology, is an important economic determinant.
Employment in the knowledge-based economy is characterised by increasing demand for more highly-skilled workers. The knowledge-intensive and high-technology parts of OECD economies tend to be the most dynamic in terms of output and employment growth. Changes in technology, and particularly the advent of information technologies, are making educated and skilled labour more valuable, and unskilled labour less so. Government policies will need more stress on upgrading human capital through promoting access to a range of skills, and especially the capacity to learn; enhancing the knowledge distribution power of the economy through collaborative networks and the diffusion of technology; and providing the enabling conditions for organisational change at the firm level to maximise the benefits of technology for productivity.
The science system, essentially public research laboratories and institutes of higher education, carries out key functions in the knowledge-based economy, including knowledge production, transmission and transfer. But the OECD science system is facing the challenge of reconciling its traditional functions of producing new knowledge through basic research and educating new generations of scientists and engineers with its newer role of collaborating with industry in the transfer of knowledge and technology. Research institutes and academia increasingly have industrial partners for financial as well as innovative purposes, but must combine this with their essential role in more generic research and education.
In general, our understanding of what is happening in the knowledge-based economy is constrained by the extent and quality of the available knowledge-related indicators. Traditional national accounts frameworks are not offering convincing explanations of trends in economic growth, productivity and employment. Development of indicators of the knowledge-based economy must start with improvements to more traditional input indicators of R&D expenditures and research personnel. Better indicators are also needed of knowledge stocks and flows, particularly relating to the diffusion of information technologies, in both manufacturing and service sectors; social and private rates of return to knowledge investments to better gauge the impact of technology on productivity and growth; the functioning of knowledge networks and national innovation systems; and the development and skilling of human capital.
1. THE KNOWLEDGE-BASED ECONOMY: TRENDS AND IMPLICATIONS
The term “knowledge-based economy” results from a fuller recognition of the role of knowledge and technology in economic growth. Knowledge, as embodied in human beings (as “human capital”) and in technology, has always been central to economic development. But only over the last few years has its relative importance been recognised, just as that importance is growing. The OECD economies are more strongly dependent on the production, distribution and use of knowledge than ever before. Output and employment are expanding fastest in high-technology industries, such as computers, electronics and aerospace. In the past decade, the high-technology share of OECD manufacturing production (Table 1) and exports (Figure 1) has more than doubled, to reach 20-25 per cent. Knowledge-intensive service sectors, such as education, communications and information, are growing even faster. Indeed, it is estimated that more than 50 per cent of Gross Domestic Product (GDP) in the major OECD economies is now knowledge-based.
Investment is thus being directed to high-technology goods and services, particularly information and communications technologies. Computers and related equipment are the fastest-growing component of tangible investment. Equally important are more intangible investments in research and development (R&D), the training of the labour force, computer software and technical expertise.
Spending on research has reached about 2.3 per cent of GDP in the OECD area. Education accounts for an average 12 per cent of OECD government expenditures, and investments in job-related training are estimated to be as high as 2.5 per cent of GDP in countries such as Germany and Austria which have apprenticeship or dual training (combining school and work) systems. Purchases of computer software, growing at a rate of 12 per cent per year since the mid-1980s, are outpacing sales of hardware. Spending on product enhancement is driving growth in knowledge-based services such as engineering studies and advertising. And balance-of-payments figures in technology show a 20 per cent increase between 1985 and 1993 in trade in patents and technology services.
It is skilled labour that is in highest demand in the OECD countries. The average unemployment rate for people with lower-secondary education is 10.5 per cent, falling to 3.8 per cent for those with university education. Although the manufacturing sector is losing jobs across the OECD, employment is growing in high-technology, science-based sectors ranging from computers to pharmaceuticals. These jobs are more highly skilled and pay higher wages than those in lower-technology sectors (e.g. textiles and food-processing). Knowledge-based jobs in service sectors are also growing strongly. Indeed, non-production or “knowledge” workers – those who do not engage in the output of physical products – are the employees in most demand in a wide range of activities, from computer technicians, through physical therapists to marketing specialists. The use of new technologies, which are the engine of longer-term gains in productivity and employment, generally improves the “skills base” of the labour force in both manufacturing and services. And it is largely because of technology that employers now pay more for knowledge than for manual work.
These trends are leading to revisions in economic theories and models, as analysis follows reality. Economists continue to search for the foundations of economic growth. Traditional “production functions” focus on labour, capital, materials and energy; knowledge and technology are external influences on production. Now analytical approaches are being developed so that knowledge can be included more directly in production functions. Investments in knowledge can increase the productive capacity of the other factors of production as well as transform them into new products and processes. And since these knowledge investments are characterised by increasing (rather than decreasing) returns, they are the key to long-term economic growth.
It is not a new idea that knowledge plays an important role in the economy. Adam Smith referred to new layers of specialists who are men of speculation and who make important contributions to the production of economically useful knowledge. Friedrich List emphasised the infrastructure and institutions which contribute to the development of productive forces through the creation and distribution of knowledge. The Schumpeterian idea of innovation as a major force of economic dynamics has been followed up by modern Schumpeterian scholars such as Galbraith, Goodwin and Hirschman. And economists such as Romer and Grossman are now developing new growth theories to explain the forces which drive long-term economic growth.
According to the neo-classical production function, returns diminish as more capital is added to the economy, an effect which may be offset, however, by the flow of new technology. Although technological progress is considered an engine of growth, there is no definition or explanation of technological processes. In new growth theory, knowledge can raise the returns on investment, which can in turn contribute to the accumulation of knowledge. It does this by stimulating more efficient methods of production organisation as well as new and improved products and services. There is thus the possibility of sustained increases in investment which can lead to continuous rises in a country's growth rate. Knowledge can also spill over from one firm or industry to another, with new ideas used repeatedly at little extra cost. Such spillovers can ease the constraints placed on growth by scarcity of capital.
Technological change raises the relative marginal productivity of capital through education and training of the labour force, investments in research and development and the creation of new managerial structures and work organisation. Analytical work on long-term economic growth shows that in the 20th century the factor of production growing most rapidly has been human capital, but there are no signs that this has reduced the rate of return to investment in education and training (Abramowitz, 1989). Investments in knowledge and capabilities are characterised by increasing (rather than decreasing) returns. These findings argue for modification of neo-classical equilibrium models – which were designed to deal with the production, exchange and use of commodities – in order to analyse the production, exchange and use of knowledge.
Incorporating knowledge into standard economic production functions is not an easy task, as this factor defies some fundamental economic principles, such as that of scarcity. Knowledge and information tend to be abundant; what is scarce is the capacity to use them in meaningful ways. Nor is knowledge easily transformed into the object of standard economic transactions. To buy knowledge and information is difficult because by definition information about the characteristics of what is sold is asymmetrically distributed between the seller and the buyer. Some kinds of knowledge can be easily reproduced and distributed at low cost to a broad set of users, which tends to undermine private ownership. Other kinds of knowledge cannot be transferred from one organisation to another or between individuals without establishing intricate linkages in terms of network and apprenticeship
relationships or investing substantial resources in the codification and transformation into information.
In order to facilitate economic analysis, distinctions can be made between different kinds of knowledge which are important in the knowledge-based economy: know-what, know-why, know-how and know-who. Knowledge is a much broader concept than information, which is generally the “know-what” and “know-why” components of knowledge. These are also the types of knowledge which come closest to being market commodities or economic resources to be fitted into economic production functions. Other types of knowledge – particularly know-how and know-who – are more “tacit knowledge” and are more difficult to codify and measure (Lundvall and Johnson, 1994).
refers to knowledge about
“facts”. How many people
à Know-why refers to scientific knowledge of the principles and laws of nature. This kind of knowledge underlies technological development and product and process advances in most industries. The production and reproduction of know-why is often organised in specialized organisations, such as research laboratories and universities. To get access to this kind of knowledge, firms have to interact with these organisations either through recruiting scientifically-trained labour or directly through contacts and joint activities.
à Know-how refers to skills or the capability to do something. Businessmen judging market prospects for a new product or a personnel manager selecting and training staff have to use their know-how. The same is true for the skilled worker operating complicated machine tools. Know-how is typically a kind of knowledge developed and kept within the border of an individual firm. One of the most important reasons for the formation of industrial networks is the need for firms to be able to share and combine elements of know-how.
à This is why know-who becomes increasingly important. Know-who involves information about who knows what and who knows how to do what. It involves the formation of special social relationships which make it possible to get access to experts and use their knowledge efficiently. It is significant in economies where skills are widely dispersed because of a highly developed division of labour among organisations and experts. For the modern manager and organisation, it is important to use this kind of knowledge in response to the acceleration in the rate of change. The know-who kind of knowledge is internal to the organisation to a higher degree than any other kind of knowledge.
Learning to master the four kinds of knowledge takes place through different channels. While know-what and know-why can be obtained through reading books, attending lectures and accessing databases, the other two kinds of knowledge are rooted primarily in practical experience. Know-how will typically be learned in situations where an apprentice follows a master and relies upon him as the authority. Know-who is learned in social practice and sometimes in specialised educational environments. It also develops in day-to-day dealings with customers, sub-contractors and independent institutes. One reason why firms engage in basic research is to acquire access to networks of academic experts crucial for their innovative capability. Know-who is socially embedded knowledge which cannot easily be transferred through formal channels of information.
The development of information technology may be regarded as a response to the need for handling the know-what and know-why portions of knowledge more effectively. Conversely, the existence of information technology and communications infrastructures gives a strong impetus to the process of codifying certain types of knowledge. All knowledge which can be codified and reduced to information can now be transmitted over long distances with very limited costs. It is the increasing codification of some elements of knowledge which have led the current era to be characterised as “the information society” – a society where a majority of workers will soon be producing, handling and distributing information or codified knowledge.
The digital revolution has intensified the move towards knowledge codification and altered the share of codified vs. tacit knowledge in the knowledge stock of the economy. Electronic networks now connect a vast array of public and private information sources, including digitised reference volumes, books, scientific journals, libraries of working papers, images, video clips, sound and voice recordings, graphical displays as well as electronic mail. These information resources, connected through various communications networks, represent the components of an emerging, universally accessible digital library.
Due to codification, knowledge is acquiring more of the properties of a commodity. Market transactions are facilitated by codification, and diffusion of knowledge is accelerated. In addition, codification is reducing the importance of additional investments to acquire further knowledge. It is creating bridges between fields and areas of competence and reducing the “dispersion” of knowledge.
These developments promise an acceleration of the rate of growth of stocks of accessible knowledge, with positive implications for economic growth. They also imply increased change in the knowledge stock due to higher rates of scrapping and obsolescence, which will put greater burdens on the economy's adjustment abilities. While information technologies are speeding up the codification of knowledge and stimulating growth in the knowledge-based economy, they have implications for the labour force.
While information technologies may be moving the border between tacit and codified knowledge, they are also increasing the importance of acquiring a range of skills or types of knowledge. In the emerging information society, a large and growing proportion of the labour force is engaged in handling information as opposed to more tangible factors of production. Computer literacy and access to network facilities tend to become more important than literacy in the traditional sense. Although the knowledge-based economy is affected by the increasing use of information technologies, it is not synonymous with the information society. The knowledge-based economy is characterised by the need for continuous learning of both codified information and the competencies to use this information.
As access to information becomes easier and less expensive, the skills and competencies relating to the selection and efficient use of information become more crucial. Tacit knowledge in the form of skills needed to handle codified knowledge is more important than ever in labour markets. Codified knowledge might be considered as the material to be transformed, and tacit knowledge, particularly know-how, as the tool for handling this material. Capabilities for selecting relevant and disregarding irrelevant information, recognising patterns in information, interpreting and decoding information as well as learning new and forgetting old skills are in increasing demand. The accumulation of tacit knowledge needed to derive maximum benefit from knowledge codified through information technologies can only be done through learning. Without investments
oriented towards both codified and tacit skill development, informational constraints may be a significant factor degrading the allocative efficiency of market economies. Workers will require both formal education and the ability to acquire and apply new theoretical and analytical knowledge; they will increasingly be paid for their codified and tacit knowledge skills rather than for manual work. Education will be the centre of the knowledge-based economy, and learning the tool of individual and organisational advancement.
This process of learning is more than just acquiring formal education. In the knowledge-based economy “learning-by-doing” is paramount. A fundamental aspect of learning is the transformation of tacit into codified knowledge and the movement back to practice where new kinds of tacit knowledge are developed. Training and learning in non-formal settings, increasingly possible due to information technologies, are more common. Firms themselves face the need to become learning organisations, continuously adapting management, organisation and skills to accommodate new technologies. They are also joined in networks, where interactive learning involving producers and users in experimentation and exchange of information is the driver of innovation (EIMS, 1994).
The knowledge-based economy places great importance on the diffusion and use of information and knowledge as well as its creation. The determinants of success of enterprises, and of national economies as a whole, is ever more reliant upon their effectiveness in gathering and utilizing knowledge. Strategic know-how and competence are being developed interactively and shared within sub-groups and networks, where know-who is significant. The economy becomes a hierarchy of networks, driven by the acceleration in the rate of change and the rate of learning. What is created is a network society, where the opportunity and capability to get access to and join knowledge- and learning-intensive relations determines the socio-economic position of individuals and firms (David and Foray, 1995).
The network characteristic of the knowledge-based economy has emerged with changes to the linear model of innovation (Figure 2). The traditional theory held that innovation is a process of discovery which proceeds via a fixed and linear sequence of phases. In this view, innovation begins with new scientific research, progresses sequentially through stages of product development, production and marketing, and terminates with the successful sale of new products, processes and services. It is now recognised that ideas for innovation can stem from many sources, including new manufacturing capabilities and recognition of market needs. Innovation can assume many forms, including incremental improvements to existing products, applications of technology to new markets and uses of new technology to serve an existing market. And the process is not completely linear. Innovation requires considerable communication among different actors – firms, laboratories, academic institutions and consumers – as well as feedback between science, engineering, product development, manufacturing and marketing.
In the knowledge-based economy, firms search for linkages to promote inter-firm interactive learning and for outside partners and networks to provide complementary assets. These relationships help firms to spread the costs and risk associated with innovation among a greater number of organisations, to gain access to new research results, to acquire key technological components of a
new product or process, and to share assets in manufacturing, marketing and distribution. As they develop new products and processes, firms determine which activities they will undertake individually, in collaboration with other firms, in collaboration with universities or research institutions, and with the support of government.
Innovation is thus the result of numerous interactions by a community of actors and institutions, which together form what are termed national innovation systems. Increasingly, these innovation systems are extending beyond national boundaries to become international. Essentially, they consist of the flows and relationships which exist among industry, government and academia in the development of science and technology. The interactions within this system influence the innovative performance of firms and economies. Of key importance is the “knowledge distribution power” of the system, or its capability to ensure timely access by innovators to the relevant stocks of knowledge. Efforts are just beginning to quantify and map the diffusion paths of knowledge and innovation in an economy – considered the new key to economic performance (Table 2).
The knowledge-based economy is marked by increasing labour market demand for more highly skilled workers, who are also enjoying wage premiums (Table 3). Studies in some countries show that the more rapid the introduction of knowledge-intensive means of production, such as those based on information technologies, the greater the demand for highly skilled workers. Other studies show that workers who use advanced technologies, or are employed in firms that have advanced technologies, are paid higher wages. This labour market preference for workers with general competencies in handling codified knowledge is having negative effects on the demand for less-skilled workers; there are concerns that these trends could exclude a large and growing proportion of the labour force from normal wage work.
Jobs Study noted a tendency in the 1980s towards a polarisation in labour
markets. In the
Three different hypotheses have been proposed to explain current labour market trends in the OECD countries: globalisation; biased technological change; and developments in firm behaviour.
à One hypothesis is that globalisation and intensified international competition have led to decreased relative demand for less-skilled workers in the OECD countries. Empirical work, however, shows that increasing imports from low-wage countries may contribute to some unemployment, but that the scale of the import increase is so limited that it could not possibly by itself explain more than a small part of the phenomenon (Katz and Murphy, 1992).
à An alternative explanation is that technological change has become more strongly biased in favour of skilled workers. The evidence is somewhat scattered, but studies of the use of information technology highlight this tendency. Data show that the polarisation of wages and employment opportunities is most dramatic in firms which have introduced computers and other forms of information technology in the workplace (Krueger, 1993; Lauritzen, 1996).
à Some scholars point to institutional change in the labour market and changes in firm behaviour as the main reason for falling real wages for low-skilled workers in some OECD countries. New high-performance workplaces and flexible enterprises stress worker qualities such as initiative, creativity, problem-solving and openness to change, and are willing to pay premiums for these skills (Figure 3). Moreover, the weakening of trade unions in some countries may have a negative impact on the relative position of the least-skilled workers,
because it has led employers to implement a low-wage strategy in which delocalisation and outsourcing are important elements.
One problem with these
hypotheses is that much of the analysis is based on
OECD countries continue to evidence a shift from industrial to post-industrial knowledge-based economies. Here, productivity and growth are largely determined by the rate of technical progress and the accumulation of knowledge. Of key importance are networks or systems which can efficiently distribute knowledge and information. The knowledge-intensive or high-technology parts of the economy tend to be the most dynamic in terms of output and employment growth, which intensifies the demand for more highly skilled workers. Learning on the part of both individuals and firms is crucial for realising the productivity potential of new technologies and longer-term economic growth.
Government policies, particularly those relating to science and technology, industry and education, will need a new emphasis in knowledge-based economies. Acknowledgement is needed of the central role of the firm, the importance of national innovation systems and the requirements for infrastructures and incentives which encourage investments in research and training (OECD, 1996b).
Among the priorities will undoubtedly be:
à Enhancing knowledge diffusion – Support to innovation will need to be broadened from “mission-oriented” science and technology projects to “diffusion-oriented” programmes. This includes providing the framework conditions for university-industry-government collaborations, promoting the diffusion of new technologies to a wide variety of sectors and firms, and facilitating the development of information infrastructures.
à Upgrading human capital – Policies will be needed to promote broad access to skills and competencies and especially the capability to learn. This includes providing broad-based formal education, establishing incentives for firms and individuals to engage in continuous training and lifelong learning, and improving the matching of labour supply and demand in terms of skill requirements.
à Promoting organisational change – Translating technological change into productivity gains will necessitate a range of firm-level organisational changes to increase flexibility, particularly relating to work arrangements, networking, multi-skilling of the labour force and decentralisation. Governments can provide the conditions and enabling infrastructures for these changes through appropriate financial, competition, information and other policies.