Can also be a theory of knowledge production where the outputs of each stage are inputs for the following stage and not the vice versa. Finally, the Linear Model is a theory of epistemology. The transfer of knowledge is seen as involving refinement and adaptation from universal principles to particular instances, from comprehensive theory to specific applications.
Innovation is taking place in distinct and sequential phases. Research is considered to be the initiating step and the source of all innovations. The Linear model suggests that the sequence from research through development to production is a standard and predominant path of innovation in both firms and national economies, and no feedback role is built into the system. It has also been used as a justification for doing basic science research in the US and provides the conventional wisdom which underlies most policy thinking about technology development and economic growth. The Linear Model of innovation, denoting serial events in time and not linearity in the sense of a linear equation, has been used to explain the link between knowledge and economic performance. Knowledge is discovered in universities, passed on to firms through publications, patents, and other forms of scientific correspondence, and to final customers in the form of a product or service. Innovation is represented as a linear process in which technological change is closely dependent upon, and generated by, prior scientific research.
Science and technology policies have evolved on government-funded R&D, whether conducted at government laboratories or in universities. Combined with the economic rationale of ‘market failure’ and Keynesian economic policies, which justified government intervention to lift and sustain the level of output and employment and to prevent another depression, government grants for research and development remain a popular policy in keeping with the Linear model.
Nonetheless, there is growing criticism of linear model. As a framework for categorizing the process of knowledge creation, the linear model diverts attention from the economic and social determinants of scientific research activity. As a theory of knowledge production, the linear model ignores the role of technology in shaping the aims, methods, and productivity of science and neglects the non-scientific origins of many technological developments. As epistemology, the linear model creates distinctions that closer examinations of scientific and technological activity fail to confirm. In addition, the linear vision of innovation dominates also the regional innovation capability evaluations. (Steinmueller, 1994)
The basic criticism of the notion that technology springs from scientific base is that supplants the complexity of the real situation of the subject. Instead it is characterized by complicated feedback mechanisms and interacting relations between science, technology, learning, production, policy and demand. However, the origins of research knowledge in basic research still lie at the core of the process. (Turney, 1991)
- Historical Background
Organized innovation was not frequent and was a slow process up to a century ago. Before 1900, there was little organized research, and individual inventors dominated the course of technological progress. The principal exception was the in-house R&D by German chemical firms, and a few major US corporations
In the First World War science was already important and the Manhattan Project was the one which emphasized the power of science and, as it seemed, “Big Science”. Many other developments on both sides, such as radar, computers, rockets and explosives, resulted from large R&D projects, mobilizing both government, industrial and academic engineers and scientists.
The experience with the scientific community in World War II was essential in establishing the widespread belief that science could make major contributions to industry. World War II attributed to the distinction of the role for the application of science in war, as well as in production.
The Linear model of innovation, with its three stages of basic research, applied research and development (R&D), became the principal model for innovation and R&D began to be used also as an interchangeable term for technological innovation. The R&D system was seen as the sources of innovations.
Though, it was pointed out that R&D was not the only source for technical change, and it was also related to other activities, such as education, design, training, production engineering, quality control, etc., nevertheless R&D measures were mostly used as a substitute for all these activities which helped to process or product innovation. (Freeman & Soete, 1997)
During the Cold War, R&D as a classification and model played a decisive role in the evolution of United States tacit technology strategy and consequently in the studies on innovation and technology development in world academic systems.
Consistent with the R&D model, postwar US federal policy for science and technology had two parts: government support for basic research, and active development of advanced technology by federal agencies in pursuit of their statutory missions. There was a strong linkage between industrial technology and public science. (Narin et al, 1997) Technology policy during the Cold War consisted basically of funding for basic research on the one hand and funding for applied research and development related to federal defense projects on the other. In addition, as a complement to the linear model, policy makers assumed that technology created in pursuit of governmental missions, especially defense, space and nuclear energy, would transfer to industry automatically and at no cost. This is the “spin-off” hypothesis that together with the linear model formed the basic framework of the US technology policy during the Cold War. (Cozzi & Impullitti, 2003)
For the first several decades after 1945, the United States emphasized the generation of new knowledge. The Linear model of innovation had also deep influence in the organizational patterns of U.S. private industries. In the 1950s and 1960s, consistent with the linear approach, an internal and hierarchical organization developed that was based on central corporate research laboratories to development to manufacturing engineering. In the 1980s that approach started being changed to a decentralized organization with carefully managed division of responsibility among R&D and engineering groups; simultaneous product and process development where possible; greater reliance on suppliers and contract engineering firms.
In the 1950s and 1960s, the overseas activities of American multinationals centered on exports and direct investment. Newer technology went abroad embodied in goods. Overseas affiliates typically got older technology. Multinational corporations kept the latest knowledge at home, where it could be protected more easily. (Freeman & Soete, 1997)
2. Public Research and Industrial Innovation
Unquestionably, there is a relationship between publicly funded basic research and economic performance which is an important one. Governments spent much money in favor of basic research in universities, institutes and elsewhere. However there is still the argument that they are not spending as much on basic scientific research as they should. According to Nelson 1959, the flow of benefits that would not have been created unless there was no flow of resources to basic science, may be defined as the social value of a given expenditure on basic research. However, the allocation of resources to science means deprivation of a flow of future benefits that would be obtained if the allocation was to other activities. In other words, there is a social cost deriving by the allocation of resources to basic science. The social profit is the difference between the social value and the social cost and he sums up by stating that the amount that should be spent is the amount of resources that maximizes social profit.
He continues notifying that since there is no perfectly competitiveness in all sectors of the economy, so as the private-profit opportunities to draw into basic research that quantity which maximizes social profit, the competitive economy will tend to spend less on that good than it should. So the existence of the market failure is what “obliges” government-funding of basic research. (Nelson, 1959)
It is commonly believed that the incentives for private investment in R&D are below the social optimum because of the public good character of knowledge or what we now call knowledge spillover effects. Besides the low appropriability of R&D-expenditure in basic research, it is assumed that small firms which operate in niche markets cannot afford large R&D laboratories. Even large firms, mostly risk-averse and short-term oriented, would not bear the large investments necessary because of indivisibility and high uncertainty. In addition, firms are constrained to financing their R&D projects by information asymmetries in financial markets (Harhoff, 1998). In sum, failure in financial and technology markets, indivisibility and economies of scale in R&D add up to a private under-investment in R&D. It is suggested that the government should finance research at public research institutions in order to attain the socially optimal R&D investment. The findings of publicly funded research are expected to be subsequently used by private businesses for industrial innovations. It follows that benefits of publicly funded research must be qualified against its cost. As this is the main justification for public funds for research at public research laboratories, economists and politicians are interested in assessing the real economic impact of publicly funded research.
3. Exogenous VS Endogenous Scientific Knowledge
Public science, according to scientists and economists, is a driving force behind high technology and economic growth. Public science can be defined as the scientific research that is performed in academic and governmental and charitable agencies. Academic research is well known as one of the major contributors to the economic growth and this has been proved by the paper provided by Narin et al, 1997. This paper examined the increasing linkage between U.S. technology and public science and proved that through more than 100,000 patent-to science references; public science plays a crucial role in patented industrial technology. The great majority of the science base of U.S. industry comes from the public sector and even the private science base is being funded by the public sector. This is reflected by the management literature on technology transfer focusing on the relationship management to public research e.g., Gemuenden and Walter, 1997. The linear model of new knowledge from publicly funded science spilling over to companies as a public good could be considered as ineffective and obsolete. For publicly funded research that directly supports industrial innovations which otherwise would not be developed by private businesses. (Mansfield, 1991)
The fear of the “market failure” is the reason why the existence of public science is essential. Under the traditional justification for public funding of research, government action serves to correct a “market failure”. The concept of market failure, rooted in neo-classical economic theory, is based on the assumption that a purely market relation would produce the optimal situation and that government policy should be limited to redressing situations where market failures have developed. (Pavitt, 1996)
In addition it is supported that without large-scale state support for research in universities, the flow of technological advances would not be adequate and this would severe the living standards of the human beings. It is said that the most useful basic research come from university departments and as Pavitt (1996) says, “Useful science is good science”.
The paper of Beise and Stahl, (1999) presents results of a survey on industrial innovations that have been made possible by academic and other publicly funded research and it tries to quantify the effects of public research on industrial innovations which is the economic justification for public research. They examined effects of firm-specific factors on the propensity of firms to use and incorporate knowledge generated by public research for these innovations. Their conclusion was that there was indeed an immediate effect on industrial innovations by public research. One of their basic findings, similar to the Mansfield’s findings in 1991, was that a considerable share of companies had identified product and process innovations, which they would not had developed in the absence of recent research of public institutions and that some of them aware in the position of naming the specific source of the research output they had used. In other words they showed that public research may transfer technology successfully to industrial companies. Technology transfer occurs through qualified academics in firms’ R&D laboratories using the knowledge they received at public research institutions. This is where big science laboratories and other non-academic public research fail. They do not spin-off much human capital, for one of their justifications is that they care for long-term research requiring low staff turnover rates.
On the other hand, the interdependence and the non-linearity are well emphasized in many references. The complexity is one of the characteristics of the innovation processes and that is why the great majority of the firms do not innovate. However, in order to gain, develop and exchange knowledge, information and resources they create interactions with other organizations. These relations are extremely complex and are characterized by feedback loops. They are not clearly characterized by linear causal relationships and this means that the systems of innovation should have the fully acknowledgment of the demand as a determinant if innovation. The demand side has been emphasized by Porter, who claims that the creation of competitive advantage is determined by the customers, the suppliers, the internal business communication and the growth of the learning process. (Edquist, 1996) For Edquist, is very important to stress the complexity and comprehensive character of innovation processes and to place innovations and learning at the very centre of focus.
Contrary to Bacon, who was the first person talking about the need of government funding, Jevons supported that technological development takes place in the research and development of industry and that “Technology builds on technology”. So, many new technologies are products of the pre-existing technology, which shows that the there is no linearity. “Basic science depends as much on advances in technology as vice versa”. (Kealey, 1996) The more basic research a firm does the greater are its profits and the dogmatic views which say that industrialists do not fund basic science because are afraid of the free ride phenomenon, or that because basic science is a public good it should be funded by government, are wrong and they do not have anything to do with reality. As Kealey writes, the science funding has nothing to do with a political decision, but it is economically determined, since there is a positive relation between the quantity and quality of a nation’s science and of its R&D. Both are strong correlated with the country’s wealth per capita.
4. The role of the public sector
As already mentioned, the motivation for public research is that private firms would not invest in research because they could not fully appropriate the profit of the findings even though the research would lead to useful industrial innovations. To identify the kind of research in place for absent private activities and to distinguish it from pure outsourcing of private R&D tasks to public research institutions, we have to stipulate that the company would not have done the R&D on their own if it had not been funded and performed by the government. It is said, that firms can only make R&D for short-term goals and not for long-term goals, which is the R&D that leads to the maintenance of the economic stability. That is another reason that emphasizes the government role in the whole subject of the industrial innovation, since innovation is not only a radical process but also an incremental one. However the main question that lies here is whether the government should better use direct or indirect policies in order to lead economy to the process of innovation more efficiently and without discouraging the individuals to innovate by themselves. In addition, the problem of the country competitiveness is also an important one, since the trend of imitating or borrowing patents is not creating national capabilities and it does not drive a country to leadership. (Freeman and Soete, 1997)
The main contribution of the government is focused on augmenting the capabilities of suppliers, producers and consumers. Government policies can prevent both the supplier-surplus and the consumer-surplus and can satisfy all.
It has been clearly stated in the historical part, that the linear model was for a long time the basic structure of the government policy. Though, the main problem that occurred was that of the “government failure”, which underestimated what the need of the market was and resulted in the imbalance of the social economy. The SAPPHO comparisons of success and failure in innovation showed that the most failures were associated with either neglect if market requirements or relatively poor understanding of the customer’s needs. (Tidd et al, 2001) As it has already been mentioned, the ideal consumer market is supposed to provide consumer with the power to choose between a variety of alternatives. Having “perfect” information and through the competitive mechanisms, consumers are able to choose the product with the better price and quality that the suppliers offer. Notwithstanding, it is widely known that there is no possibility for this ideal scenario and for that in many countries anti-monopoly and consumer legislation attempt to decrease the consumers vampirism by the producers and the suppliers. (Freeman and Soete, 1997)
Instead of leaving the market to act on its own and not to promote the social welfare, there are institutions that constitute constraints and motives for innovation and that are shaping the general movements of the firms. Such incentives are laws, health regulations, cultural norms, social rules and technical standards. (Nelson, 1996) It is out of question for the firms to invest in projects that do not enclose the characteristics of appropriability and non-rivalry. Firms cannot prevent the leakage of knowledge to other organizations, and that means they cannot keep all the benefits from an innovation to themselves. That is why government is expected to fund most activities toward basic research, while firms fund most development. The existence of the uncertainty and the changing environment are reluctant factors for a firm in order to make its own R&D.
According to Martin and Salter (2001), one benefit from publicly funded research is the augment of useful knowledge. Public funding of basic research expands the scientific information available for firms to draw upon their technological activities. But there is a strong complementary relationship between public and private research systems. The two systems are interlinked by common interests, institutional affiliations and personal connections. They identify skilled graduates as another benefit that flows to firms by the publicly funded research. These graduates have the ability to expand tacit knowledge, solve complex problems, and perform research. In addition, a key output of public funded basic research is the creation of new instrumentation and methodologies, but it has not yet been evaluated as it is difficult to recognize that contribution of the government-funded research. The chance for individuals and organizations to participate in the global community of research and technological community is given by the governments, while there is evidence that firms find other ways of creating informal networks. Government policy lies under the need of creating bridges of communication and exchange of knowledge. Another important contribution of the public-funded research is that helps industry and others to solve complex problems. Finally, it is said that government funding in research can attribute to the creation of new firms and in general in new employment since it gives motives for innovation and the problem of the unemployment will not occur. (Martin and Salter, 2001)
5. Conclusion
“The rate and direction of the development of a country’s science base is strongly influenced by its level of economic development, and the composition of its economic and social activities. In other words, it is socially shaped”. (Pavitt, 1998, p. 793)
Unquestionably, the debate of whether public sector should intervene or not in the process of the knowledge transfer, it cannot be answered here, since the aim of this essay was to put down the conflicting views of many scientists. The basic framework is that, government should fund the basic research which is related with the sectors of health, environment, and safety and of course government should be responsible to protect intellectual rights without taking advantage of its power of monopoly.
To sum up, it is important to mention that the public sector in relation with the private sector should act as complementary aspects of the economy in order to set forward the social welfare and the economic stability. Nowadays, innovation is a core process for a nation to get developed and not only to be a follower in a global economy, when country competitiveness is as important as defense was in the World War II.
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