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1. Increasing Division Of Labor In Knowledge Production And Use
The growth of research and development activities (R & D) reﬂects the increasing division of labor in the production and use of scientiﬁc and technological knowledge—a process foreseen by Adam Smith at the beginning of the Industrial Revolution. Since then, professional education, the establishment of laboratories, and improvements in techniques of measurement and experimentation have progressively increased the eﬃciency of discovery, invention, and innovation (Price 1984, Mowery and Rosenberg 1989). Three complementary forms of specialization have developed in parallel, each contributing to the growth of R & D.
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1.1 Specialization By Discipline: The Growth Of Science And Engineering
First, progress and specialization in scientiﬁc disciplines accelerated in the nineteenth century with the development of more powerful research tools and techniques. Increasing opportunities for application also led to the emergence of the engineering disciplines: hence chemical engineering in addition to applied chemistry, and electrical engineering in addition to applied physics (Rosenberg and Nelson 1994). The diﬀerences in timing of the emergence of new opportunities for innovation reﬂected radical but uneven improvements in the knowledge base underlying technological change, and in particular the emergence of new technological paradigms (Freeman et al. 1982, Dosi 1982).
The mechanical paradigm was the basis of the Industrial Revolution. It did not grow out of contemporaneous scientiﬁc advances, but of improvements in the quality of metals and the precision with which they could be formed and machined. These enabled the design, Development, and testing of prototypes of families of machines with greatly improved performance based on materials of homogeneous and predictable quality, and on shapes with compatible sizes. Similarly, the initial improvements in metals processing technologies depended less on scientiﬁc understanding than on Development activities, experimenting with diﬀerent alloys and processing conditions in pilot plant. Even today, such development activities in prototypes and pilot plant typically account for about three quarters of the R & D expenditures of private business ﬁrms and for about two-thirds of total R & D.
1.2 Specialization By Corporate Function: The Growth Of Business R & D
The science-based chemical paradigm (based increasingly on synthetic chemistry) and the electrical paradigm (based on electromagnetism and radio waves) laid the basis for the industrial R & D laboratory, initially in the chemical and electrical ﬁrms in Germany and the USA. Many of the initial applications—like the use of techniques of chemical analysis to control the quality and composition of materials in the increasingly large-scale processing industries— were relatively mundane, but very proﬁtable in reducing costs. Management learned progressively that the science-based technological opportunities were applicable over a range of existing and new product markets, and therefore opened up opportunities for what is now called ‘related’ product diversiﬁcation. Mowery and Rosenberg (1989) have described the spread of the establishment of R & D laboratories in the USA from the chemical industry to other sectors, and from larger to smaller ﬁrms. Similar processes have been at work in Europe, and more recently in East Asia (Caron et al. 1995, Nelson 1993).
Thus, in addition to the beneﬁts of the cognitive division of labor into more specialized ﬁelds, the functional division of labor within business ﬁrms also augmented the rate of technical change. Corporate R & D laboratories and similar groups devoted fulltime to inventive and innovative activities provided an eﬀective method for creating, combining, and coordinating increasingly specialized knowledge. They provided improved and specialized instrumentation, which enabled ﬁrms to monitor and beneﬁt more systematically and eﬀectively from advances in specialized academic disciplines. They also created skills in the development and testing of laboratory concepts and prototypes, and the translation into commercialized products. Firms were able to experiment with a wider range of products and processes than had previously been possible when constrained by established products and production lines. In ﬁelds rich in technological opportunity, ﬁrms have in consequence become multiproduct as well as multitechnological.
Technological paradigms have been associated with the emergence of large dynamic ﬁrms that have been successful in exploiting the new opportunities. The largest R & D spenders today are in companies that grew with the emergence of the mechanical (and automobile), chemical, and electrical– electronic paradigms. Aerospace is a special case, having been technologically force-fed, especially since World War Two, by government R & D subsidies and procurement linked to military requirements. The fastest growing R & D spenders today are those closely associated with ICTs and software technology.
1.3 Specialization By Institution: The Growth Of Academic Research
In the nineteenth century, de Tocqueville foresaw that the dynamics of capitalist competition would greatly stimulate the development of innovative activities that showed the prospect of a commercial return. He also argued that public authorities would need to support complementary public research of a more fundamental nature, in order to avoid diminishing returns, to open up new opportunities, and to provide trained researchers. This has happened too. In all advanced countries governments have become the main source of the funding of research activities, and related postgraduate training, in universities and similar institutions. Corporate R & D laboratories have come to depend increasingly on a supply of scientists and engineers aware of the latest research results and trained in the latest research techniques (Salter and Martin 2001).
1.4 R & D And Modernization
This historical pattern of specialization and growth in knowledge production has been broadly repeated in the processes of modernization of late-coming countries, and is observable in countries at diﬀerent levels of development today: R & D expenditures as a percentage of Gross Domestic Product (GDP) increase with GDP per head, both in speciﬁc countries over time, and in cross-sections of countries at any point in time. In successful modernizing countries, R & D is preceded by systematic business investments in improvement-generating activities: in particular, in production engineering, quality control, and design activities, initially making minor modiﬁcations and improvements, and later becoming the basis for indigenous innovative activities (Lall 1992, Bell 1984). At this stage, business-funded R & D increases rapidly, accompanied by the growth of university-based research in underlying disciplines, with both reﬂected in the growth in the numbers of international patents and scientiﬁc papers. This pattern can be observed most clearly in both South Korea and Taiwan during the 1980s and 1990s.
The centrally planned Soviet model of modernization, practiced in the former USSR and imposed or adopted elsewhere, gave high priority to R & D. By the late 1950s and early 1960s, R & D expenditures in Central and Eastern European countries were apparently higher than those in Western Europe and the USA. Certain Western observers, therefore, concluded that the Soviet system was superior in promoting R & D and technical change. However, Soviet economic performance subsequently deteriorated, and it later became clear that a very high proportion of Soviet R & D was oriented towards weapons development, and that the government-established R & D laboratories established for each industry were decoupled from the requirements of producers and consumers (Hansen and Pavitt 1987). The major reductions in R & D activities since their collapse in 1989 can be seen as painful adjustments to make R & D activities—and the underlying activities in production engineering, quality control, and design—become an integral part of a process of economic modernization (Dyker and Radosevic 1999).
The Soviet system also had inadequate linkages with technical advance in the rest of the world economy. One important feature distinguishing today’s modernizing countries from those of the nineteenth century is the availability of more productive technologies in more advanced countries. Countries successful in assimilating these more advanced technologies have had two characteristics (Hobday 1995): ﬁrst, strong linkages with the more advanced countries’ technology whether through inward direct investment (e.g., Singapore), inward technology licensing by locally owned ﬁrms (e.g., Japan, S. Korea), or subcontracting agreements from advanced countries to local ﬁrms (e.g., Taiwan); second, the development of local, change generating activities, culminating in R & D activities, that were essential inputs to eﬀective imitation, as well as to innovation (Cohen and Levinthal 1989).
2. Measurement Of R & D Activities
2.1 Patterns Of R & D Activity
By the beginning of the 1960s, initiatives by the US National Science Foundation and the Organization of Economic Co-operation and Development (OECD) had established common deﬁnitions of R & D activities, and led to the collection by governments of systematic data on R & D activities. These have since been complemented by privately funded surveys comparing the R & D activities of individual business ﬁrms. They show the following common and largely invariant features of R & D activities.
(a) In industrially advanced countries, business and government are the main sources of funds for R & D activities. Business funding is in general larger, and spent in-house mainly on applied research and development activities. Government funding is divided between basic research performed mainly in university-type institutes, and various types of R & D associated with health, the environment, defense, and the support of industry and agriculture. This R & D is performed mainly in the laboratories of government agencies and business ﬁrms.
(b) In the industrially advanced countries, the share of GDP typically spent on R & D varies between 1.5 and 3.0 percent of Gross Domestic Product (GDP), compared to 0.5 and 1.5 percent in the newly industrializing countries, and less than 0.5 percent in the rest. The share of national R & D funded and performed by business ﬁrms tends to increase along with GDP per head.
(c) More than 60 percent of all business-funded R & D is typically performed in the chemical, electrical, electronic, and automobile industries. The largest individual corporate spenders on R & D are the world’s leading automobile, electrical, and ICT (information and communication technologies) ﬁrms.
2.2 The Economic Determinants And Impact Of R & D Activities
The improved quality of R & D statistics has enabled economists and other analysts to deepen understanding of both the determinants and the economic impact of R & D activities, at the level of countries, industries, and ﬁrms. A number of analysts have been able to show that—amongst the industrially advanced countries—diﬀerences in the levels and rates of growth of national R & D activities have a signiﬁcant inﬂuence on diﬀerences in national performance in exports and productivity (Fagerberg 1987).
At the industry level, considerable attention has been given to the eﬀects of ﬁrm size and industrial structure on R & D activities. Given the dependence of specialization on scale, the proportion of ﬁrms performing R & D increases with ﬁrm size. However, there is no clear consensus on how R & D intensity varies with ﬁrm size amongst large ﬁrms: evidence can be found either way. And although R & D is found mainly in concentrated industries, there is compelling evidence that variations amongst industries in both the degree of concentration and R & D intensity are determined jointly by a third factor, namely, interindustry variations in the extent of technological opportunities (Levin et al. 1985).
Less progress has been made so far in measuring the eﬀects of diﬀerences in R & D expenditures on company performance. This is partly because comprehensive and comparable R & D data at the company level are only slowly becoming available. It is also because of the diﬃculty of deﬁning a proper measure of corporate performance. Those used include the R & D production function, stock market evaluation, and long-term growth (Patel 2000).
Sections 2.1 and 2.2 and show that statistics on R & D activities can be a useful proxy measure for innovative activities. But they have their limitations, the most often mentioned of which is that they measure inputs and not outputs. Equally, if not more important are the following:
(a) In large ﬁrms, R & D statistics do not measure the often considerable expenditures on complementary activities in production and marketing, that are necessary to transform the outputs of R & D into commercially successful innovations.
(b) In small ﬁrms, they do not measure part-time innovative activities, which are particularly important in the machinery and software sectors.
(c) They capture only very imperfectly the growing volume of innovative activities in software now being performed in ﬁrms in service sectors, such as ﬁnance and distribution.
Other indicators of knowledge-generating and innovative activities have therefore been developed to complement R & D indicators, the most important of which have been counts of patents, papers, citations, and numbers of innovations (van Raan 1988).
3. Some Contemporary Debates In R & D Management
Many of the characteristics and problems of managing corporate R & D have changed very little since the nineteenth century.
(a) The need to orchestrate and integrate specialized knowledge and skills across disciplines, professions, functions, and divisions.
(b) The progressive improvement in fundamental scientiﬁc understanding, accompanying the increasing systemic complexity of innovations—a process that will continue with the more widespread application of the techniques emerging from ICT.
(c) The diﬃculty (impossibility?) of making reliable predictions about the success or otherwise of speciﬁc innovations, especially major ones.
At the same time, new problems and challenges have emerged.
(a) With increasing specialization in both the production of knowledge, and of the components of increasingly complex systems, ﬁrms are faced with increasingly diﬃcult choices about what products and knowledge to outsource, and what to retain in-house. An important part of the in-house R & D function is now devoted to the monitoring and co-ordination of innovative and production activities external to the ﬁrm.
(b) In addition to the well-established function of supporting foreign production, large ﬁrms are performing a growing share of their R & D outside their home country, in order to tap into the increasingly numerous international sources of leading-edge scientiﬁc and technical advance. This poses new challenges for managers in integrating skills and knowledge over long distances (Niosi 1999), and for national policy-makers in assessing the location of the beneﬁts of public investments in academic research.
(c) There is some evidence that academic research is becoming increasingly linked to commercial R & D activities. For some, this is the consequence of unwelcome ﬁnancial pressure from governments on universities to demonstrate short term ‘relevance’ in their research. For others, it is the consequence of fundamental changes in the locus of knowledge production. Other evidence suggests that reductions in the costs of technical experimentation through simulation software now make it easier for academic researchers to develop and test experimental prototypes.
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