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Technological innovation is the successful implementation (in commerce or management) of a technical idea new to the institution creating it. Innovations are distinguished from inventions, technology and research, but may arise from any of the three. A variety of models of the innovation process are described, for they are useful in developing public policies for encouraging innovations as well as for managing their creation. The more advanced of these models include consideration of complementary assets and social capital, which helps explain the diﬀerences in innovative capacity in diﬀerent societies. The American society is particularly given to the use of banners under which to rally public opinion to the advance of economic well being. In the middle 1970s, when ‘high tech’ industries emerged as the key to growth, and American ﬁrms were immediately challenged by the technically adroit Japanese, the banner was ‘critical technologies’ derived from defense and space research. When the economic challenge became serious in the 1980s and early 1990s the banner was ‘competitiveness’; even conservative President Reagan launched a White House taskforce to suggest how government could enhance American competitiveness in the face of serious price and quality competition in technology intensive industries, especially in Asia. As we prepare to enter the next millenium, the new banner, in nations rich and poor, is ‘innovation.’
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While a ﬁrm can become more competitive by cornering a market or slashing worker’s wages, innovation implies a transformation in the market—the invocation of imagination and daring in the adoption of new ways of doing things. The word innovation has an old history. The Oxford English Dictionary uses a broad deﬁnition: ‘A change in the nature or fashion of anything; something newly introduced, a novel practice, method, etc.’ and traces its ﬁrst use back to 1553. In its contemporary usage, Burke is quoted as writing in 1796 ‘It is a revolt of innovation; and thereby the very elements of society have been unfounded and dissipated.’ In modern usage we must distinguish innovation from invention, technology, and scientiﬁc or engineering research. Invention is the conception of a new artifact or process that is useful, original, and non-obvious. Technology is the capability to perform a technical task or process. Research leads to understanding of how things work. Innovation, as deﬁned by Richard Nelson (1993), is ‘the processes by which ﬁrms master and get into practice product designs and manufacturing processes that are new to them …’ Thus, an invention does not become an innovation (and many never do) until the invention is successfully embodied in a product and introduced to the market.
Even then, an innovation does not necessarily make a successful contribution to the economy. As David Teece (1987) observed, many products that embody little novelty are successful in the market place, while innovations that are not supported by a variety of ‘complementary assets’ may fail. The complementary assets of an innovation are all the requisite ingredients of success that are not provided by the innovator and may not be readily available in society because of the novelty inherent in the innovation. Thus, the ﬁrst personal computers became wildly successful only after a cottage industry provided a wide variety of software applications. A new drug cannot make money for its innovator until the manufacturer receives approval from government regulators.
Nelson’s deﬁnition requires that an innovation be new, at least to the innovator, and that it must be in production and use, but it does not have to embody an invention or be the result of any research. Thus, many of the innovations with the greatest impact on society were marketing, institutional, or managerial innovations. The Sears Roebuck catalog revolutionized marketing to families in a predominantly agricultural society. The corporate research laboratory that ﬂowered at GE, DuPont, and ATT early in the twentieth century provided a more productive way to create useful technology. Just-in-time manufacturing is a Japanese managerial innovation that reduces cost and accelerates product cycles and quality control. This research paper focuses on technical innovation—that class of innovations based on technical novelty.
2. Technical Innovation Models
The popular imagination is excited by the creation of new ﬁrms by the marriage of daring investors with the dreams of inventors and other would-be innovators. The US economy is noteworthy for the dynamism of its venture capital industry, and new research breakthroughs often capture the imagination with their economic potential. Thus, when materials that could conduct electricity without any resistance and do so at or near room temperature were discovered (and the inventors were rewarded with Nobel Prizes) the potential to destabilize the entire electrical machinery industry was in everyone’s mind. After over a decade of dashed hopes, ﬁnally a company has mastered a technology to make superconducting motors that operate at temperature far above liquid helium temperature. They have a contract to sell such motors to the US navy.
The innovation process that follows such a discovery is described by the time honored, but oversimpliﬁed ‘linear model’ of innovation, in which technical innovations begin with a scientiﬁc discovery or an invention. The idea is then explored through a period of applied research. When the technology is suﬃciently understood, the work is transferred to product and process development, followed by production, quality control, distribution and marketing. This is a reasonable description of one way a new invention arising from scientiﬁc research may be exploited. Scott Shane (2000) has shown that the most radical or fundamental inventions patented and licensed by MIT are most likely to be successfully exploited in a new ﬁrm, created by investors for the purpose. Such radical innovations often must create their own markets. However, technical innovations do not always arise from a scientiﬁc breakthrough; they are quite frequently the response of technically clever people to an identiﬁed market need. This is reﬂected in the saying ‘necessity is the mother of invention.’ The transistor was a discovery in search of a more economical switch for telephone exchanges, and the integrated circuit was the answer to the excessive power consumption, size, and manufacturing cost of computers made of discrete electrical elements. In these examples, as in many other cases of science-based innovations, the new capability not only solves the identiﬁed need, but does much more, creating new markets or even entirely new industries. Innovations are compounded both of answers looking for questions and questions looking for answers. In the real world both are intimately linked. This fact gives rise to the ‘chain link’ or ‘spiral’ models of innovation in which new ideas are stimulated by new market needs, which in turn are extended when the capabilities of the innovation are better understood (Kline and Rosenberg, 1996). Thus, it is rare that a technically radical innovation is introduced into a totally new market. The more typical trajectory is interative. First a new market is found for an existing technology (a market innovation); then new technology is brought to this new market (a technical innovation), and so forth.
At the level of product development, an analogous interaction takes place, between research to understand the new technology and product development to deﬁne product performance and cost. Thus when an invention is being reduced to commercial practice, one must know what the product speciﬁcations (function and cost) will be in order to know what tests to apply. But function and cost cannot be known until the technology is developed. This iterative process describes almost all incremental or evolutionary innovation in existing companies.
3. Innovation As A Socioeconomic Process
Futurists have often called attention to the remarkable fact that progress in meeting many of the needs of society does not improve linearly with time, but rather exponentially. Thus, if one plots on semi-log graph paper the speed of commercial transportation against the year of introduction, from the horse-drawn trolley, to the train, the airplane, and the rocket, one gets a surprisingly straight line. The same observation is inherent in Moore’s Law, which observes that the density (and hence speed divided by cost) of integrated circuits has doubled every 18 months for many years and continues to do so (Lester 1998). What accounts for this remarkable attribute of technical innovations? It is not inherent in the nature of technical progress, but rather is the result of the socioeconomic dynamics of an economy that rewards innovation. Consider the typical time history of a radical innovation arising, let us say, from new university research. After a promising discovery there is typically a period of intense excitement. The most daring investors leap into the business, hoping to acquire that ‘ﬁrst mover’ advantage and intellectual property protection that the economist Schumpeter recognized as necessary if a ﬁrm hoped to gain enough proﬁt to repay the risks and costs of innovation. Then after perhaps 5 to 7 years the recalcitrance of nature becomes widely evident; the low hanging fruit has been plucked, and the number of ﬁrms decreases sharply—through failure, merger, or switch to a more conventional product opportunity. Those who persevere in pursuit of commercial advantage from the discovery and have the requisite ﬁnancial staying power and the technical skill and knowledge may then master and reduce to practice the technology required for the innovation. The business may then take oﬀ with exponential growth as the technology matures, costs fall, and new applications for the technology are found. Investors and inventors alike observe the exponential growth of the business and invest their money and their imaginations in the expectation that exponential growth will continue.
Sooner or later the chosen technical approach becomes increasingly diﬃcult to improve, given the limitations imposed by real materials and the laws of natural science. Continued rate of performance growth and cost reduction slows; the technology is reaching its natural limits. The curve of progress vs. time starts to become S shaped. The gap between expectation and reality begins to widen, and a huge incentive to ﬁnd another technology that can satisfy the future expectation for improvements in product function and cost is created. Because science has made such extraordinary advances in the last half century, the potential for invention is enormous. It is the reward of ﬁlling the expectation gap that converts that potential to another innovation. Thus, another S-shaped curve becomes tangent to the ﬁrst one, and the exponential growth in capability and in economic activity continues unabated. In this way performance advances seamlessly from horse to auto, to airplane, to rockets. Similarly Moore’s Law continues to be valid despite evolution from vacuum tubes to single transistors, to integrated circuits of every increasing complexity.
4. National Systems Of Innovation: Social Capital
Because innovation is a socioeconomic as well as a technical process, one might expect diﬀerent societies to exhibit diﬀerent strengths and weaknesses in their capacity for innovation. Indeed this is true, as observed by many students of comparative innovation policy. As Patel and Pavitt (1994) pointed out, the economic theory prevailing in the 1960s predicted that buoyant demand and an open trading system would allow the international (and domestic) diﬀusion of technology and this would lead to equalization of technological performance of the industrial nations at the national level. This prediction, they argued, was based on a ﬂawed model of science-based development, indeed of technological change. It presupposed that technical change would be fully determined by investments in better machinery, the diﬀusion of public technical information, and the acquisition of ‘tacit’ knowledge resulting from relatively costless ‘learning by doing.’ If this model were equally applicable to all countries in a similar state of development, it would follow that the gaps between the US economy, and that of Japan, the United Kingdom, Germany, France should have closed rather rapidly. It has not happened. Japan and Germany have moved ahead; the UK and France have fallen behind. Taiwan, Korea, and Singapore have leapt ahead from a very backward state 30 years ago. Brazil, Mexico, and India, all in better economic health than the Asian Tigers at the end of World War II, have failed to do so to the same extent. These three assumptions in the 1960s economic model have persisted, in more recent years, in the form of a Cold War paradigm of the innovation process. It was widely believed in the US government (as well as in the UK and France) that one could gain commercial advantage by force-feeding industrial technical development in pursuit of government missions. This is the ‘spinoﬀ’ theory of defense industrial research. Defense research investments, under this theory, would bring into existence new machinery, abundant and accessible new technical knowledge, and the private sector could quickly assimilate the embedded knowledge by ‘learning by doing.’ The problem with the three post-war economic assumptions is that the eﬃciency of each of these processes varies strongly from one national socioeconomic setting to another. Patel and Pavitt conclude that technology diﬀusion, productivity learning, and transfer of embodied technology have large transaction costs when they encounter cultural, managerial, and institutional barriers. It is the absence of these barriers and the presence of eﬃciently functioning networks connecting innovators, investors, producers, supporting service providers and consumers that largely govern the beneﬁts that ﬂow from technical innovations. These attributes of the economy are referred to as ‘social capital.’ Richard Nelson’s ambitious study entitled National Systems of Innovation (Nelson 1993) examined the policies and institutional settings for innovation in 14 countries. It is clear that the structure of economies, socioeconomic policies, cultural factors, and natural endowments all inﬂuence the environment for innovation. In addition, Nelson recognizes that innovation systems may not be national, but rather sectoral or regional. For example, the world oil industry shows little variation in its innovation practices from country to country, while it diﬀers signiﬁcantly from other industries in all countries. The levels of trust that exist among entrepreneurs, the ﬁnancial sector, government and industry leaders are as inﬂuential in the capacity of a society to innovate as is the role of education and the participation of higher educational institutions in the nation’s research and invention activities. As ﬁrms turn away from vertical integration and increasingly look to global sources of innovation to keep them competitive, issues of social capital will become more important. The methods of microeconomics are still essential but are no longer suﬃcient to understand why some societies are more innovative than others. Thus the importance of social capital forces the study of innovation beyond the boundaries of the ﬁrm into an understanding of the complex relationships among interdependent players in a high-tech economy.
Henry Ergas addressed this problem by deﬁning a model of the innovation process at the level of the economy, rather than of the ﬁrm (Ergas 1989). His model is also a dynamic one, in that it incorporates the response of the economy to the introduction of an innovation, which in turn will aﬀect the next generation of the innovation. Ergas sees four parts to the innovation process:
(a) Generation—all the activities from technical and market concepts to introduction into manufacturing, in other words virtually all of the activity calling for research and development skills.
(b) Application—commercialization: manufacturing learning, introduction of a complete product line and system of distribution, up to initial customer acceptance.
(c) Verticalization—the responses of suppliers, distributors, providers of complementary assets, and of competitors to the introduction of the innovation, responses that will, in turn, change the innovation and the way it is received.
(d) Diﬀusion—the responses of the rest of the socioeconomic environment, especially the way the innovation changes the end user’s behavior. One can then expect user organizations, and perhaps society as a whole, to be transformed to the degree the innovation has that power (as for example the personal computer accomplished). Society then may change regulations and laws, introduce new curriculae in schools, and eventually modify the culture. Thus the next round of innovation takes place in a new environment calling for still more creativity.
5. Role Of Governments
Fostering innovation and entrepreneurship is not a natural role for governments. As Nathan Rosenberg and L. E. Birdzell, Jr. (1985) recognized in their classic book, How the West Grew Rich,
In all well-ordered societies, political authority is dedicated to stability, security, and the status quo. It is thus singularly illqualiﬁed to direct or channel activity intended to produce instability, insecurity and change.
Nevertheless, promoting innovation and entrepreneurship is increasingly seen as a pro-active responsibility of government. Nations that once relied on science and technology policy, by which they usually meant public investments in scientiﬁc research, came to realize that this supply-side policy would probably be ineﬀective without demand-side policies to put those ideas to work. Thus, there is now widespread acceptance of the idea that Science and Technology Policy should be replaced by a Research and Innovation Policy (Branscomb and Keller 1998).
The goals of an innovation policy are clear enough, even if the means for their attainment are not: full employment, decreased income disparities, rising real incomes, safe, healthy working conditions, and satisfying work. What policy tools, other than investing in research, can one use to encourage innovation? The list is long: economic policy, trade policy, tax policy and accounting rules, competition policy, regulation of equity markets and industry structure, intellectual property law, industrial relations, education and training, and the full range of environmental, health, and safety regulations.
This list of policy tools would seem to oﬀer states a lot of options. In fact these policies must also be seen as a set of potential barriers to innovation, set up one behind the other. Any one of them, if suﬃciently mismanaged, can seriously discourage would-be innovators. It might seem obvious that all these economic issues should be dealt with by economic policy makers who should appreciate the fragility of an economy increasingly based on science-based innovation. But science policy experts have for so long insisted (erroneously) that innovations happen automatically as a result of research, that economists have mostly left these issues to ‘science policy.’ And science policy does not enjoy a priority on political agendas any where near economic, trade, tax, or regulatory policy. Furthermore, only a few of these policy tools (intellectual property law is an example) can be used to create a positive, speciﬁc incentive to innovation; most exist for other reasons and must be examined to ensure that suppression of innovation is not an unwanted side eﬀect. To ensure that every government agency is alert to this responsibility, it may be most eﬀective to entrust a policy body at or near the top of government with monitoring agency diligence. The challenge to governments is formidable, not only for the reasons given by Rosenberg and Birdzell but because, as discussed earlier, building an innovative society requires developing the social capital of society, a task that most governments perform poorly or are reluctant to even attempt. Thus, whatever the quality of the social capital, innovations must still come from the creativity, imagination, and determination of individuals who want to change the way things are.
- Branscomb L M, Keller J 1998 Towards a research and innovation policy. In: Lewis M, Branscomb L M, Keller J (eds.) Investing in Innovation: Creating a Research and Innovation Policy that Works. National Academy Press, Cambridge, MA, pp. 462–496.
- Ergas H 1989 Global Technology and National Politics unpublished. Quoted by permission in Young Hwan Choi Y-H,
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