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The Sources and Rate of Technological Change in the U.S. Economy Technological change is often difficult to predict, and its employment and productivity consequences usually are felt gradually rather than suddenly. Although the pace of technological change affects employment and productivity growth, the impact of new technologies also is affected heavily by organizational, institutional, and social factors. A central reason for the complex, gradual character of the employment, productiv- ity, and other economic effects of such change is that these impacts are felt only through the adoption of new technologies by individuals and firms. In light of this fact, we devote considerable attention in this chapter to the process of adopting new technologies. DEFINING TECHNOLOGICAL CHANGE Technological change has two major effects: (1) it transforms the processes by which inputs (including labor and materials) are converted into goods and services, and (2) it enables the production of entirely new goods and services. Process innovation is technological change that improves the efficiency with which inputs are transformed into out- puts; product innovation results in the production of new goods. The distinction between process and product innovation often is hazy. New products, such as the transistor, frequently require significant process innovations before they can be produced economically. Con- versely, the potential cost reductions offered by many new manufactur- ing processes may be realized only after the products to which they are 24

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SOURCES AND RATE OF TECHNOLOGICAL CHANGE 25 applied have been redesigned. In addition, an innovative product developed by one firm for example, computer numerically controlled machine tools- may be transformed into a process innovation when it is adopted by another firm. Product innovations may serve entirely new markets; consequently, their effects are notoriously unpredictable. (Chapter 4 explores the uncertainty surrounding predictions of the employment consequences of process innovations.) Repeatedly, technological forecasts have failed to foresee the size and nature of the markets for new products. Computers are a classic example. Howard Aiken, one of the developers of the electronic computer in the 1940s, was skeptical about the plans of J. Presper Eckert and John Mauchly to launch commercial computer production; Aiken predicted that the total U.S. market would be no more than four or five machines. Internal IBM studies conducted prior to the firm's decision to begin computer production were equally pessimistic; according to the studies, the market for the "tape processing machine" would amount to roughly 25 units (Ceruzzi, 19861. The record of techno- logical advance contains many such examples (Rosenberg, 1983~. Invention, Innovation, and Diffusion The history of scientific discoveries like penicillin or x rays contributes to a popular perception that technological change is a process of dramatic breakthroughs. In fact, it might better be described as incremental and consisting of several stages, extending well beyond the moment of scientific discovery. The invention stage includes the discovery of a scientific or technological advance and its translation into a prototype- for example, a working model. Invention, which subsumes basic re- search, must be distinguished from innovation, which includes the processes of advanced development (e.g., "scaling up" a pilot plant for commercial-volume production). In the case of the transistor, an impor- tant product innovation that has been fundamental to modern technolog- ical advance, invention spanned the period from the late 1930s, when Bell Telephone Laboratories inaugurated its program of basic research in solid-state physics, through 1947, when the first model of a point-contact transistor was produced by Bardeen, Brattain, and Schockley (see Braun and MacDonald, 1978; Mowery, 1983; Nelson, 1962; Tilton, 1971~. The innovation stage that saw the translation of this crude invention into a commercially marketable product occurred during 1947-1954. This stage included significant advances in the theory of semiconductors and in materials refining and processing. Advances in both the theory of mate- rials and in production techniques for making pure silicon crystals

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26 TECHNOLOGY AND EMPLOYMENT contributed to the introduction by Texas Instruments of the silicon junction transistor in 1954. The diffusion of an innovation (discussed in detail later in this chap- ter) refers to the period of its adoption by users. Once again using transistors as an example, the diffusion that began once the product was introduced commercially in 1954 has continued to the present day; moreover, during this period, transistors have undergone considerable modification in design and production. Chaudhari (1986) described the dramatic advances since 1960 in the miniaturization of transistor com- ponents, focusing on the shrinkage in the width of "lines" that connect the transistor to other electronic components: "A typical line width in 1960 was 30 micrometers.... Today line widths are commonly on the order of one micrometer. . ." (p. 1371. Among other significant ad- vances during the diffusion stage was the development of the planar process for manufacturing integrated circuits and other solid-state components. Each of these stages invention, innovation, and diffusion consists of a series of interacting phases; within the invention stage, for example, basic research often is heavily influenced by applied research findings (see Kline and Rosenberg, 1986; Rosenberg, 1983~. Moreover, the invention, innovation, and diffusion processes themselves are linked in a complex fashion, which can be seen in the extensive modifications that are often made to an innovation during its diffusion. In the case of the transistor, the innovation stage of its development required fundamental research, just as its application to new uses during the diffusion stage has required investments in applications engineering and fundamental research. Influences on Invention, Innovation, and Diffusion Despite the close links among them, the invention, innovation, and diffusion stages of a technology appear to respond to different influences that are not always easy to distinguish. In the case of invention, for example, the factors affecting individual genius simply are not well understood. These stages also may be carried out by different individuals or organizations. In many instances, the inventor of a new product or process does not develop and market it. The original inventors of the computer, for example, were not employees of the firm that proved most successful at developing, improving, and marketing the device. Another case is that of DuPont. Many of the most significant innovations com- mercialized by DuPont prior to the invention of nylon during the 1920s and 1930s were based on patents purchased from other firms and individuals, rather than on the inventions of its employees.

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SOURCES AND RATE OF TECHNOLOGICAL CHANGE 27 Compared with invention, innovation is a far more costly stage of technological change. ~ It is likely therefore to be affected by such economic factors as the investment climate, rates of capital formation, or expectations of the location and size of future markets. The diffusion of innovations, which is discussed later in this chapter, appears to be influenced by cost considerations, uncertainty, and other factors unique to specific markets, such as regulations that affect the structure of the market for an innovation. For example, the regulation of pharmaceuticals and air transportation and the availability of third-party payments for medical services have affected the speed and the extent of new technol- ogy diffusion in those industries. Moreover, inasmuch as the diffusion of new technology is the result of decisions to invest in machinery or products that embody a technology, the rate of diffusion of innovations is affected by factors that determine the rates of net investment within an economy, including the domestic savings rate, the cost of capital, depreciation practices, and price stability. The Interaction of Technological and Organizational Change Technological change creates new options for the performance of specific functions. Yet the precise organization of these functions or the skill requirements associated with them are seldom determined solely by the characteristics of the technology. Organizational factors strongly influence the implementation of new technologies and their effects on skill requirements, quality of worklife, productivity, and profitability. Indeed, the potential improvements offered by many innovations often can be realized only if there are complementary organizational changes. For example, redesigning products often allows more profitable use of many new computer-based manufacturing technologies. After installing equipment for computer-integrated production of lawn and garden trac- tors, Deere and Company realized substantial savings by redesigning its products to allow a single component design to be used in eight different tractors.2 Other firms have redesigned their products for easier automated assembly; a recent IBM desktop printer has been so simplified for automated assembly that it can be manually assembled in minutes. "'Development" alone, which is the portion of innovation incorporating most of the activities of production engineering and tooling, typically accounted for more than 65 percent of privately financed U.S. R&D investments annually during 1960-1985 (National Science Foundation, 1985, Appendix Tables 2-3 and 2-9). 2Remarks by G. R. Sutherland of Deere and Company at a meeting of the Panel on Technology and Employment, April 25, 1986.

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28 TECHNOLOG Y AND EMPLO YMENT (Lehnerd, 1987, discusses similar changes in the design of Black and Decker power tools.) Such integration of production engineering and product design often demands extensive organizational change. The National Research Council's Committee on the Effective Implementation of Advanced Manufacturing Technology (1986) noted in its report that computer- integrated manufacturing (CIM) requires that "Edjecisions once made by people in functions that were relatively independent must now be made jointly. Efforts to design the product and process simultaneously, for example, require product engineering and manufacturing engineering to work closely together" (p. 29~. Although CIM has not yet been widely adopted in U.S. manufacturing, its requirements for organizational adap- tation are by no means unique. A number of other computer-aided manufacturing technologies impose similar organizational demands. In many cases, once a new technology has been adopted, the resulting improvements in the quality of a firm's manufactures and its productivity come as much from the reorganization of production and other activities required by the adoption as they do from the technologies themselves. For example, management personnel interviewed by panel members and staff in the course of this study argued that the organizational changes necessary to adopt computer-aided manufacturing processes yielded savings as great as those realized from this new production technology itself (the IBM printer described previously is one example). In most cases, these organizational changes were necessary to introduce com- puter-aided technologies. The converse was not true, however the reorganization of design, engineering, and production processes did not require new technologies. The value and importance of attention to the organizational dimensions of technological change, then, cannot be overstated. Indeed, without such attention, the potential profitability or product quality benefits of new technology may not be realized. Prior to the extensive use of advanced computer-aided or computer-integrated manufacturing technologies, Jap- anese automotive firms, for example, achieved great advances in produc- tivity and product quality mainly through organizational techniques. The best-known of these successes, the Toyota production system, was developed during the 1960s and 1970s, prior to the development of CIM and robotics; it used production technologies that did not differ signifi- cantly from those of U.S. automobile manufacturers at the time (Abeg- glen and Stalk, 19861. Within the U.S. automotive industry, General Motors (GM) offers dramatic plant-level contrasts in productivity and product quality that illustrate the importance of organizational factors in realizing the potential of new technology. In Fremont, California, the joint venture between GM

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SOURCES AND RATE OF TECHNOLOGICAL CHANGE 29 and Toyota (known as New United Motor Manufacturing, Inc. NUMMI) uses modest levels of factory automation that are embedded in the Toyota production system manned by a unionized work force; thus far, NUMMI has been extraordinarily successful in meeting production and quality targets. By contrast, GM's factory in Hamtramck, Michigan, which uses advanced factory automation technologies, operates at roughly 50 percent of its planned capacity and has experienced serious quality problems (Nag, 1986; Womack, in press). Qualitative and anecdotal evidence suggests that, in the past, U.S. management and labor have been insufficiently attentive to the need to reorganize design and work processes to support technological change. Jaikumar (1986) presented data that illustrate this point in his analysis of 35 "flexible" manufacturing systems (i.e., systems that use computer- aided machinery and "work cells" to produce a wide variety of products at low cost) in the United States and 60 such installations in Japan. He concluded that: Rather than narrowing the competitive gap with Japan, the technology of automation is widening it further.... With few exceptions, the flexible manufacturing systems installed in the United States show an astonishing lack of flexibility. In many cases, they perform worse than the conventional technology they replace. The technology itself is not to blame; it is management that makes the difference. Compared with Japanese systems, those in the U.S. plants produce an order-of-magnitude less variety of parts. Furthermore, they cannot run untended for a whole shift, are not integrated with the rest of their factories, and are less reliable. Even the good ones form, at best, a small oasis in a desert of mediocrity. (p. 69) U.S. managers and workers must understand that the "rules of the game" of international competition and technology's role within that competition have changed. Automation and firm and factory reorgani- zation are means to the end of higher-quality, lower-cost products. Achieving this goal requires attention to production technology, product design, and work organization. Without such attention, the payoffs from the adoption of new technologies will be realized slowly or not at all. Measuring Technological Change If we could measure the rates of invention, innovation, and diffusion in the U.S. economy, we could simplify greatly the analysis of technology's impact on employment. Such measurements, however, are far from simple. The United States and most other industrial nations do not collect systematic time series data on the rates of diffusion of specific new technologies. As a result, there are few reliable data or indices with which

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30 TECHNOLOGY AND EMPLOYMENT to measure such rates. Measuring the rates of invention or innovation also is hampered by the fact that the outputs of these stages are extraordinarily difficult to measure. Those indices that have been used-the number of patents, publications, or expert tabulations of technologically and com- mercially significant innovations have serious shortcomings. For exam- ple, a widely used gauge of inventive or innovative activity, R&D investment, measures only inputs into invention and innovation, rather than outputs. Without output measures, we cannot assess the efficiency with which investments in science and technology are translated into inventions or innovations. A further inadequacy of R&D investment as a measure is that it includes development expenditures; such expenditures affect both invention and innovation, as well as diffusion, and thus do not allow for separate measurement of these stages. Other commonly used proxies for the rate of technological change include increases in the joint productivity of capital and labor- that is, "total" or "multifactor" productivity growth. Multifactor productivity growth measures improvements in the efficiency with which inputs are translated into outputs and thus should be responsive to changes in the rates of new technology generation and adoption. As a gauge of techno- logical change, however, this index has several defects. Empirically, multifactor productivity growth is derived as a residual that is, after adjusting for contributions made to greater output by increases in the quality and quantity of capital and labor. As a residual, it is a measure of ignorance, an index of the contributions to output growth of unmeasured influences rather than a direct measure of technological change. In addition, like all productivity indexes, measures of multifactor produc- tivity are sensitive to fluctuations in the level of economic activity. To reduce the influence of such fluctuations, multifactor productivity growth typically is measured across business cycles. An alternative productivity measure that does not account for improvements in the productivity of capital inputs is labor productivity growth, measured as growth in output per hour. During most of the postwar period, these two measures have exhibited similar trends; since 1973 rates of growth in both labor and multifactor productivity have been much lower than in the 1950s and 1960s (Gullickson and Harper, 1986~. Using productivity growth as an index of the rate of technological change has other drawbacks. Many factors other than technology influ- ence investment and diffusion, the processes that underpin productivity advance. The low savings rate in the United States, for example, may increase the cost of capital to private firms, thus lowering net investment and impeding diffusion and productivity growth. Furthermore, in measur- ing productivity change, it is often difficult to adjust measures of physical output for changes in the quality of products. Should a modern computer

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SOURCES AND RATE OF TECHNOLOGICAL CHANGE 31 be treated as identical in quality to the machines of the mid-1950s? In theory, quality adjustments should be made frequently, but the data requirements for such a task are so great that until recently, the output data compiled by the Bureau of Economic Analysis (BEA) of the U.S. Department of Commerce, which historically have been used by the Bureau of Labor Statistics (BLS) for productivity measurement, did not incorporate adjustments for improvements in product quality. In 1985 BEA developed a computer price index that adjusted computers for quality; the new index resulted in dramatic declines in the estimated costs of such equipment after 1972, and it also will affect measured productivity growth for this period (Cole et al., 1986; Slater, 19861. This is merely one example of the complexity involved in analyzing and measuring the relationship between technological change and productivity growth. Much of the current concern over the effects of technological change on employment is based on the belief that the rate of such change whether it is defined as innovation or diffusion has increased in recent years. Although specific technologies (e.g., office automation) may be experi- encing more rapid change or diffusion now than in the past, aggregate indicators suggest that there has been no across-the-board increase in the rates of innovation or diffusion of technologies. The rate of growth in the number of patents granted within the United States (i.e., the number of inventions deemed novel and therefore patentable by the U.S. Patent Office) was lower during the early 1980s than during the late 1960s.3 The average annual rate of growth in patent grants was 3.7 percent during 1965-1970, -0.1 percent during 1970-1975, 0.1 percent during 1975-1980, and 1 percent during 1980-1984 (National Science Foundation, 1985, Table 4-81. In another study, Baily (1986) examined technological change in several industries, including the research-intensive chemicals industry, and concluded that innovation actually may have slowed in these indus- tries in the past decade, resulting in lower rates of productivity growth. Measures of diffusion rates are, if anything, even more difficult to obtain than measures of the rates of invention or innovation. What work there has been in this area lends support to the conclusion that diffusion rates are not increasing. Mansfield (1966), for example, found little or no support for the hypothesis that the rate of diffusion had increased during the post-World War II period. The National Research Council's Panel on Technology and Women's Employment (1986) also expressed skepticism about the claim that diffusion rates of information technologies are likely to increase: "In the panel's judgment, diffusion will not accelerate over 3To avoid deceptive, short-run fluctuations as a result of changes in the length of time required to process patent applications, patents were dated by the year in which they were applied for rather than the year in which they were granted.

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32 TECHNOLOGYAND EMPLOYMENT the next ten years: deliberate rather than headlong speed seems likely" (p. 641. As noted previously, measures of multifactor or labor productiv- ity growth, which incorporate the impacts of changes in rates of innova- tion and diffusion, also have been lower since 1973. (See Chapter 3 for an extended discussion of productivity.) The rates of invention, innovation, and diffusion within the U.S. economy thus do not appear to have increased during the past two decades. Nevertheless, the widely perceived increases in the employ- ment-displacing effects of technological change on the U.S. economy, which have generated increased concern over the employment impacts of technological change, may reflect shifts in the geographic location of innovative activity. For much of the 1950s and 1960s, the United States commanded a considerable technological lead over European industrial nations and Japan. Since then, the technological dominance of the United States has declined somewhat (see "The Diffusion of Technology" later in this chapter). Foreign governments and enterprises now are important sources of new technology as well as leaders in its adoption (see the next section). As a result, there is an increased likelihood that innovation and diffusion will occur either initially or more rapidly in other countries, enhancing the competitiveness of foreign producers. As the sources of new technologies and the location of their initial application continue to broaden internationally, the displacement of U.S. workers due to more rapid foreign technology adoption or innovation may occur more frequently and more quickly- although there may be no change in the underlying worldwide rate of innovation. Moreover, the pace at which technologies are transferred within the international economy and thus become available to foreign firms now appears to be more rapid than in previous decades (Abramovitz, 1986; Baumol, 1986; Mansfield and Romeo, 1980; Organisation for Economic Co-operation and Development, 19791. Indeed, Baumol suggests that the increased speed of international technol- ogy transfer is partly responsible for convergence in productivity growth rates among industrialized nations. SOURCES OF TECHNOLOGICAL CHANGE Although individual inventors continue to play a role in the U.S. innovation system, their importance as a source of new technology has declined considerably over the course of this century (Schmookler, 1957~. Broadly speaking, there are now three main sources of U.S. technological change that is, three sources of financial support for the development and application of new technologies within the U.S. economy: (1) industrially financed R&D; (2) R&D financed by the federal government and performed in industry, university, and government laboratories; and (3)

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SOURCES AND RATE OF TECHNOLOGICAL CHANGE 33 55 In 50 - c, Cal - o In o ._ = ._ m - ~n LU fir: cat is x 45 40 35 30 25 20 15, . O . 1 960 f 1965 1970 1975 YEAR 1980 1 985-86 Estimates FIGURE 2-1 Industry expenditures on R&D, 1960-1986. SOURCE: National Science Foundation (1985, 1986a). foreign R&D, both privately and publicly funded. The relative importance of these three sources has shifted over time and changed substantially during the postwar period. Two significant changes since the 1960s include reduc- tions in the importance of federally financed defense R&D for commercial innovation and an increase in the amount of foreign R&D. Industrially Funded Research and Development in the United States A large share (3~50 percent during the postwar period) of the total U.S. R&D investment is industrial research expenditures (National Science Foundation, 19851. Figure 2-1 depicts trends (in 1982 dollars) during 1960-1986 in industrially funded R&D.After growing throughout the 1960s at an annual rate of more than 6 percent, industrial R&D spending scarcely grew at all during the early 1970s; after 1975 it began to climb again.4 4The deflator (i.e., the index used to convert these figures into 1982 dollars, which is the implicit gross national product deflator) used in Figure 2-1 may understate growth in the costs of R&D somewhat (Mansfield, 1984). This means that some of the apparent rebound in real R&D spending after 1974 may be illusory. In addition, as Cordes (1986) notes, industrial R&D spending as a share of sales declined from 1970 to 1978; after 1978, growth resumed.

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34 TECHNOLOGY AND EMPLOYMENT Empirical research suggests that industrially funded R&D yields significant improvements in productivity. Mansfield's (1972) summary of a number of industry studies concluded that productivity growth was directly related to the level of R&D investment. Griliches (1985) conducted a statistical analysis of a large sample of firms, concluding that higher levels of privately financed R&D were associated with higher rates of productivity growth. Mansfield (1980b) found that the share of "long-term" or basic R&D within privately financed R&D was associ- ated positively with productivity growth within both industries and firms. (See also Mansfield, 1980a, for a summary of this research.) These and other studies suggest that the benefits of R&D investment are realized only after a lag of 3-6 years (the lag is greater for basic research investments), which reflects the length of time needed to embody R&D results in innovations and market or adopt the innovations. Thus, the detrimental effects of the slowdown in industrial R&D spending during the early 1970s have been felt within the past S-10 years; the benefits of the renewed growth in R&D investment after 1975 have probably been realized only since 1980. Neither the slowdown in industrial R&D investment during the early 1970s nor its resurgence in the late 1970s and early 1980s have been satisfactorily explained. For example, there is little evidence that the lower U.S. R&D investment of the early 1970s was the result of less favorable tax treatment. Neither can we explain the recent resurgence of growth in R&D investment by the more lenient treatment of R&D under the tax code; the resurgence in R&D investment substantially predates the passage of the R&D tax credit in 1981. (See Cordes, 1986, for a summary of the evidence for these conclusions.) Clearly, the recent recovery in U.S. R&D growth is a positive eco- nomic development, but when measured as a share of the gross national product (GNP), privately financed U.S. R&D lags behind that of such nations as Japan and West Germany. In 1984, the last year for which comparable data are available, the GNP shares for industry-financed R&D were 1.3, 1.S, and 1.7 percent, respectively, in the United States, West Germany, and Japan. For the GNP share of privately financed U.S. R&D to match the GNP share of privately financed Japanese R&D investment, U.S. industry would have to increase its 1984 R&D spending (roughly $49 billion) by approximately $15 billion more than 30 percent of privately financed U.S. R&D in 1984 (National Science Foundation, 1986a). Although some scholars (e.g., Brooks, 198S) have criticized the use of GNP shares as a basis for comparing national R&D investments, this measure captures the concept of R&D investment as a necessary cost of competing in the modern world economy as a developer or adopter of new technologies. In contrast to its competitors, U.S. industry appears to

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40 TECHNOLOG Y AND EMPLO YMENT 2.75 2.50 ~ 225 Z O 2.00 A: As Do: CL 1.75 West Germany ~ ~United States Japan ~ 1.00 ' United Kingdom France 1985 U.S. NONDEFENSE R&D EXPENDITURES = $74.6 BILLION 1 1 1971 1975 1980 1985 1986 YEAR (est.) FIGURE 2-5 Nondefense R&D expenditures as a percentage of gross national product (GNP) by country. SOURCE: National Science Foundation (1987). Although R&D investment is an important source of technological innovation, as the previous discussion noted, the firm or nation under- taking such investment does not always receive a majority or (in some cases) any of the profits from its investment. As scientific and technical data and research results spread throughout the world more quickly, the ability of a single firm or nation to "appropriate" all the financial or competitive fruits of its R&D investment has declined. Sustained support for the generation of new knowledge remains critically important in the current world economic environment. What is now of equal importance, however, is the ability of a firm to move rapidly from invention to commercial application and the ability of a national economy to adopt new technologies quickly, thus narrowing the gap between current and "best" practices. R&D investment positively influences the adoption and rapid exploitation of new technologies; these activities are discussed in the next section. THE DIFFUSION OF TECHNOLOGY The economic effects of new technology, whether revealed in produc- tivity growth, creation or loss of jobs, or changes in wages and profits, are realized only through its adoption. Therefore, no analysis of the effects of

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SOURCES AND RATE OF TECHNOLOGICAL CHANGE 41 new manufacturing and office technologies on U.S. economic perform- ance and employment is complete without considering technology diffu- sion that is, the factors that affect the speed and extent of adoption of innovations. Perhaps the most striking aspect of diffusion, and the factor that most complicates the task of forecasting the employment and economic im- pacts of new technologies, is its gradualness.6 It can take decades for all of the members of a given industry, firm, or sector to adopt an innovation. Enos (1962) found that the period between the invention of a new process or product and its initial application (in other words, substantially prior to its extensive utilization) averaged 14 years for one sample of inventions; in another study, Mansfield (1961) found that, for 9 of 12 innovations, adoption by all of the large firms in the coal mining, railroad, brewing, and iron and steel industries took more than 10 years. There are several reasons why diffusion is such a lengthy process. Prospective adopters often find it difficult to evaluate new technologies; as a result, they are uncertain about the benefits and costs involved and may be reluctant to adopt a new technology rapidly. Moreover, the transmission and absorption of the information necessary to adopt an innovation require considerable time. Adopting a specific innovation may also demand extensive complementary investments in new plants and equipment and in work force training and retraining. Finally, the age and other characteristics of the existing capital stock in potential adopter firms affect the attractiveness of investing in a new technology. Factors Affecting the Diffusion of Technology Theoretical and empirical studies of technology diffusion suggest that two broad factors influence the rate of diffusion of technologies: (1) uncertainty surrounding the characteristics of a new technology and the payoffs from adopting it, and (2) the actual profitability of its adoption. Sociologists such as Rogers (1983) and economists such as Griliches (1957, 1960) and Mansfield (1961, 1963b, 1966) have defined the charac- teristic s-shaped curve describing the diffusion of an innovation: plotted against time, the proportion of adopters within a population increases slowly, then accelerates, and finally levels off (Figure 2-61. These re- searchers suggest that the adoption of a technology by a growing number of firms or individuals progressively reduces uncertainty and increases 6The fact that the economic and employment consequences of new technologies frequently are felt more gradually than economic change induced by other causes, such as currency fluctuations or natural disasters, should simplify the development of policies to aid worker adjustment (see Chapter 7).

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42 TECHNOLOG Y AND EMPLO YMENT o 1 o CL O I 1~ ,~ Z ~ _ Z ~ Lll a c' O O: cat - - / / TIME FIGURE 2-6 Time path of the diffusion of a "typical" innovation. the amount of information available to potential adopters, thereby accel- erating adoption, until a large fraction of the relevant population has adopted the innovation. Firm size also affects the speed with which an innovation is adopted. Mansfield (1963a) found that large firms adopted innovations more rapidly than small firms and attributed this difference to the larger in-house engineering and scientific staff and financial resources of the bigger firms, among other factors. Diffusion rates vary across industries and technologies as a result of structural and other factors that affect the profitability of adoption and the level of uncertainty about such profitability. For example, government regulation can play a role either in increasing or slowing diffusion. Regulation of U.S. commercial air transportation prior to 1978 supported rapid diffusion of new commercial aircraft among the passenger airlines by encouraging competition based on service quality rather than on price (Jordan, 1970; Mowery, 19851; in another case, more stringent regulation since 1962 appears to have slowed the introduction and

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SOURCES AND RATE OF TECHNOLOGICAL CHANGE 43 diffusion of new pharmaceuticals in the United States (Schwartzman, 1976~. There are limits, however, to what can be determined about technology diffusion from the available data. Most empirical studies of diffusion focus on cross-sectional differences in the adoption of a single innovation, which restricts the ability to predict diffusion rates for multiple innovations over time. Thus, little is known about the determi- nants of aggregate trends in diffusion rates within an economy. Any analysis of the diffusion of innovations is further complicated by the fact that an innovation often is greatly modified in the course of its diffusion (Rosenberg, 1976~. Examining the diffusion of computers during the past four decades, for example, involves analyzing the diffusion of a number of very different products, each of which has been modified drastically since its introduction the capabilities of the original personal computers differed greatly from those of subsequent microcomputers, and these products bear little if any resemblance to the mainframe behemoths of the 1950s and 1960s. Another limitation in any analysis of diffusion rates is that empirical studies have focused on manufacturing, health care, or agriculture there are few studies of the diffusion of innovations within the services sector outside of health care. The service industry diffusion studies that have been performed (e.g., Stoneman, 1976, who considered the diffusion of computers within British banks) confirm the importance of profitability and information as key determinants of the rate at which productivity- enhancing innovations are adopted. Although the specific impediments to diffusion within the service industries may differ somewhat from those observed within manufacturing, the general determinants of the rate of diffusion appear to be quite similar across the two sectors. How do the diffusion rates of specific technologies in manufacturing and services compare? U.S. industry's use of advanced manufacturing technologies, including robotics and computer numerically controlled machine tools, seems to be increasing at a rate comparable to the rates of diffusion of earlier process innovations such as mainframe computers. The number of robots in U.S. industry, for example, grew at an average rate of roughly 40 percent per year during 1981-1985, although this growth appears to have slowed recently.7 The number of robots per 1,000 manufacturing employees (a figure including white-collar workers) grew from 0.1 in 1976 to 1.3 in 1986 (J. Bernstein, Robotic Industries Associ- ation, personal communication, 1987; Flamm, 19861. Moreover, and of greater significance for the long-run employment impacts of technological 7Flamm (1986); see also "GM Throws a Monkey Wrench Into the Robot Market, Business Week, August 25, 1986.

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44 TECHNOLOGY AND EMPLOYMENT change in U.S. manufacturing, both the level of use and the rate of adoption of such productivity-enhancing innovations as robotics and computer numerically controlled machine tools within U.S. industry appear to be lagging behind those of many industrial competitors, notably Japan, Sweden, and West Germany (Flamm, 1986; Mowery, 1986; Technology Management Center, 19851. Jaikumar (1986) estimates that "[iln the last five years, Japan has outspent the United States two to one in automation. During that time, 55% of the machine tools introduced in Japan were computer numerically controlled (CNC) machines, key parts of FMSs [flexible manufacturing systems]. In the United States, the figure was only 18~o" (p. 701. The differences that can be observed among the United States and other nations in the rates of diffusion and use of robotics are not well explained by differences in wage rates, capital costs, or industry mix in U.S. and foreign economies (Flamm, 19861. The empirical evidence on rates of adoption (Mansfield, 1963b) also suggests that small U.S. firms are likely to be even further behind the technological "frontier" than large firms. This is a matter of some concern; the competitive and technological vitality of smaller firms is important for overall U.S. employment and competitiveness because of the roles such firms play as employers (see Chapter 6) and as suppliers to larger manufacturing firms. Data on rates of investment by U.S. firms in office automation and information technologies suggest that diffusion of these technologies may be occurring somewhat more rapidly than the diffusion of some new manufacturing technologies. In the early 1980s, the rate of growth in the use of computer workstations (on-line terminals and workplace personal computers), which are predominantly found in nonmanufacturing settings (Harris, 1983), was higher than that for robots. As Figure 2-7 indicates, the number of U.S. workstations has increased from approximately 675,000 in 1976 to roughly 28 million in 1986, an average growth rate of 47 percent per year.8 The number of workstations has grown from 15.4 for every 1,000 white-collar employees in 1976 to 450 per 1,000 white-collar workers in 1986. Obstacles to the Diffusion of Technology Before a firm can adopt many of the computer-based office and manufacturing technologies of interest to this panel, it must overcome a number of obstacles, which reflect the factors mentioned earlier as important influences on the diffusion of technology. The obstacles a firm 8Letter of January 8, 1987, to Dennis Houlihan from Donald C. Bellomy, editor of International Data Corporation's computer industry report The Gray Sheet.

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SOURCES AND RATE OF TECHNOLOGICAL CHANGE 45 28 26 24 an o - ._ - 20 O 18 16 5e 1 4 o Em: LU m I 22 12 10 8 6 4 2 O4 f of' / 1 1 1 1 1 1 1 1 1975 1977 1979 1981 1983 1985 YEAR FIGURE 2-7 Growth in the number of U.S. workstations (on-line terminals and nonhome personal computers), 1975-1986. SOURCE: Donald C. Bellomy, International Data Corpo- ration, personal communication, January 8, 1987. faces can be grouped into three broad and overlapping categories: (1) adoption costs, (2) product standards, and (3) the availability and evalu- ation of relevant information. The adoption costs associated with computer-based technologies that integrate numerous separate operations are in many cases greater than those associated with discrete innovations with less demanding integra- tion requirements. Often, the technologies that underpin many of these computer-based innovations are new to the industries and firms faced with an adoption decision a factor that heightens the uncertainties about the technology and increases the costs of acquiring the necessary exper- tise for its evaluation and operation. Uncertainty and hence costs are also increased by rapid changes in these technologies. The substantial costs of the applications engineering necessary for adoption are likely to be particularly onerous for smaller firms, which may have few or no specialized technical personnel on their payrolls. A related impediment contributing to higher adoption costs stems from the fact that higher-level skills are often required for successful adop- tion in the early stages of the introduction of new technologies. A number of scholars (Barter and Lichtenberg, 1987; Nelson and Phelps,

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46 TECHNOLOGYAND EMPLOYMENT 1966; Nelson et al., 1967) argue that the installation and "debugging" of complex machinery for which little operating experience has been com- piled are frequently lengthy processes, requiring specialized skills and in many cases extensive scientific or technical training: The observers of the early production of transistors remarked on the high percentage of physicists and engineers required to control the processes. As experience accumulated, however, it became possible to design machines to do some of the jobs formerly requiring highly educated talent, and to develop training programs to teach less educated workers the special things that they needed to know to be effective workers. (Nelson et al., 1967, p. 106) A highly skilled work force can adopt new technologies more rapidly. Nonetheless, the high costs of training may impede the diffusion of technologies in the United States; this is especially true if firms and workers are unable to develop contractual agreements to share the costs and benefits (in terms of higher productivity, higher wages, or product quality) of retraining investments (Bendick and Egan, 19821. Moreover, these retraining costs may place heavy burdens on small firms. Sweden and Japan have been leaders in the adoption of computer-based manu- facturing technologies and robotics, and both have labor market institu- tions and practices that may support higher levels of investment in training for their blue-collar work forces (see Chapter 71. Such invest- ments may aid the faster adoption of some key manufacturing technolo- gies in these nations. Product standards play a central role in the development and adoption of information and computer technologies. Within the United States, standards in information technologies historically have been set by market forces rather than by a governmental or industry-wide group. For example, standards for computers were largely established by IBM, reflecting its dominance of the market. For other technologies (e.g., office automation or computer-based manufacturing), no single vendor domi- nates the market; as a result, standards have been slower to emerge, despite the activities of the Corporation for Open Systems and the American National Standards Institute. Because standards lessen the need for large investments in applications engineering to modify interfaces among incompatible pieces of hardware or software, they lower adoption costs and aid the adoption of new technologies. In view of the salience of these costs for small firms, standards are likely to be particularly useful in helping small firms adopt new technologies. Once established, however, a product or process standard may have an extremely powerful influence over the future direction of technological change. Uninformed or hasty standardization may effectively "lock in" an inefficient technology (David, 19851. The

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SOURCES AND RATE OF TECHNOLOGICAL CHANGE 47 lack of standards thus retards diffusion, whereas their premature or ill-informed establishment increases the risks of technological suboptimi- zation. Prospective adopters of computer-based technologies in manufacturing and services often face problems in evaluating the cost consequences of adoption. Many of the essential areas in which these process technologies yield significant cost savings are not incorporated in conventional invest- ment analyses because of conceptual flaws in these analytic frameworks. For example, reductions in inventory or work in progress have been singled out by several researchers as important dimensions of resource savings that are ignored by accounting systems developed for the evalu- ation of discrete investment decisions (see Ettlie, 1985, 1986; Kaplan, 1986; Technology Management Center, 19851. In some instances, U.S. managers are not sufficiently familiar with a new technology to evaluate its performance effectively. Improving management education may be one way to provide the familiarity and analytic skills necessary for informed evaluations of new technologies. KEY TECHNOLOGY "CLUSTERS" The preceding sections of this chapter have discussed technology in general terms. What specific technologies will affect employment and the workplace in the next 10-15 years? Brief descriptions of several salient technologies follow; our discussion of them focuses on trends in technolog- ical development and adoption and their employment implications. Four technology "clusters" are considered: information technologies; computer- aided manufacturing technologies (robotics, CIM, and flexible manufactur- ing systems); materials; and biotechnology. Many of the important innova- tions in all four of these technology clusters are well beyond the invention stage and are now undergoing development for commercial applications. This list is not comprehensive, nor are the items on the list mutually exclusive-information technologies, for example, are critical to CIM, and innovations in materials underpin both information technologies and computer-aided manufacturing processes. The panel considered these tech- nologies to be worthy of particular attention because of the widespread notice each has received as well as their potential for widespread application within the U.S. economy in the near future. Information Technologies One of the most important structural changes in the U.S. economy, a change that affects both the manufacturing and services sectors, has been the rapid development and application of information technologies (i.e.,

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48 TECHNOLOGY AND EMPLOYMENT technologies that store, retrieve, analyze, or transmit information). Com- puters, telecommunications equipment, and the microelectronic compo- nents on which they rely are included in this cluster. Within many sectors of the modern economy, information is an increasingly important input to the production of goods and often reduces the amount of labor and the quantity of other inputs required per unit of output.9 Information has also become an increasingly valuable commodity in its own right. The evi- dence (e.g., U.S. Bureau of Labor Statistics, 1986b) suggests that the development of these technologies should enhance the demand for workers who manipulate and analyze information, relative to the demand for workers who enter and collate data. Computer-Aided Manufacturing Technologies The incorporation of computer- and microelectronics-based technologies within manufacturing has transformed the work environment in some industries and firms while simultaneously contributing to public concern over job displacement. These technologies include robotics, computer-aided design and manufacturing, and microelectronics-based, machine-controlled technologies such as computer numerically controlled machine tools. Current estimates of the rates of development and diffusion of these technologies in a wide range of functions suggest that they are unlikely to produce mass displacement of workers during the next decade or two. Moreover, according to some analysts (Cyert, 1985; Sanderson, 1987), computer-aided technologies could support growth rather than reductions in U.S. manufacturing employment: the reduced direct labor costs made possible by these technologies may allow some U.S. firms to move assembly and fabrication operations back to the United States from low-wage areas of the world. Most public concern about these technologies focuses on the displacement of production workers. Widespread adoption of computer- aided manufacturing technologies, however, is also affecting middle-level engineers and managers, as Chapter 6 notes. Advanced Materials Fundamental to progress in microelectronics and information technol- ogies, as well as to many areas of manufacturing and the services sector, are advances in such materials as ceramics (including high-temperature 9Freeman and Soete (1985) argue that "it is this feature which distinguishes IT [information technology] so clearly from 'old-fashioned' automation. Some of the most significant productivity gains linked to the introduction of IT relate to more efficient inventory control, as well as significant energy, materials, and capital savings" (p. 55).

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SOURCES AND RATE OF TECHNOLOGICAL CHANGE 49 superconducting materials), nonmetallic composites, and polymers. In- novations in materials technology affect employment in several ways. First, they may reduce markets for the materials they replace. On the other hand, markets for the new materials may expand and create new employment. The net employment effect of such a substitution is deter- mined by the comparative labor requirements per unit of output for the two materials, as well as the relative size and rates of growth in the respective markets. Materials innovations also may affect labor require- ments for processing and fabricating materials. Currently, however, the magnitude and even the direction of these employment effects are uncertain. Biotechnology The U.S. Congress's Office of Technology Assessment (1984) defines biotechnologies as technologies that use living organisms to modify plants or animals and develop microorganisms for specific purposes.~ Biotech- nology arguably is the least advanced of the four clusters, reflecting its recent development and the impediments to its rapid diffusion. The sectors in which these technologies initially will be introduced the pharmaceutical and chemical industries, agriculture, and environmental protection do not employ large numbers of people, leading us to conclude that the near-term aggregate employment impacts of biotech- nologies will be modest and will primarily influence shifts within profes- sional and technical occupations. SUMMARY The pace of technology diffusion governs the rate at which the economic and employment effects of new technologies are realized. The data discussed in this chapter suggest that within the U.S. manufacturing sector, the pace of adoption of some new technologies is slower and the levels of utilization lower than in some other industrial nations. This slower rate of adoption within U.S. manufacturing may allay concerns over the job-displacing impacts of rapid technological change, but it actually carries a false assurance. Because foreign firms are adopting Patois definition is by no means universally accepted. The National Research Council's Board on Agriculture (1987) defines biotechnology as "the use of technologies based on living systems to develop commercial processes and products. . . [including] the tech- niques of recombinant DNA, gene transfer, embryo manipulation and transfer, plant regeneration, cell culture, monoclonal antibodies, and bioprocess engineering" (p. 3). Other analysts (Miller and Young, 1987) reject any effort to develop a definition of biotechnology.

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50 TECHNOLOGY AND EMPLOYMENT these technologies more rapidly than U.S. firms and are expanding their shares of the U.S. and world markets, job displacement from the slow adoption by U.S. firms of these productivity-increasing manufacturing technologies is likely to be more serious than any displacement resulting from rapid adoption; the recent surge in import penetration of many U.S. manufacturing industries provides support for this assertion (see Chapter 3 for additional discussion). U.S. industry must operate closer to the technological frontier if this nation is to maintain high employment levels and living standards.