The Emergence of Technological Paradigms: The Evolutionary Process of Science and Technology in Economic Development

When discussing advances in science and technology, it is necessary to divide each stock and flow clearly. That is, existing scientific or technological knowledge is a ‘stock’, and advances in scientific or technological knowledge are a ‘flow’. Although the knowledge of science or technology is a state function and it can accumulate, the progress of science or technology is a process and is transitional. [With regard to this paragraph, see also Kline (1990) and Stokes (1997)].

Needless to say, scientists may obtain economic rewards through IPR or academic spin-offs.

Although there are many engineers who do not personally operate for economic reward, they aim for the economic reward of their company.

It goes without saying that Price did not deny that science and technology have interacted.

Although Chesbrough (2003) illustrates the relationship between science and technology (research and development) in order to compare ‘closed innovation’ with ‘open innovation’, the relationship takes a linear form in his model.

Stokes’s model does not illustrate the technological paradigms.

A technological paradigm is a ‘“model” and a “pattern” of solution of selected technological problems, based on selected principles derived from natural sciences and on selected material technologies’; a technological trajectory is ‘the pattern of “normal” problem solving activity (i.e. of “progress”) on the ground of a technological paradigm’ (Dosi 1982, p. 152).

Although, in Yamaguchi’s diagram, technology, such as the refinement method of a hermetic art, and knowledge of a chemical reaction are contained in ‘knowledge creation’, they are not contained in ‘science’ in this paper.

The problems of the Bush model (linear model) are pointed out in Sect. 4.

Whether these advances are improvements along a technological trajectory or a shift in paradigm, with new technological trajectories emerging, depends on whether the ‘selected scientific knowledge’ as the basis of the technological trajectory is new or not (even if scientific knowledge precedes technological knowledge as in the Bush model, or technological knowledge precedes scientific knowledge as in the Rosenberg model).

See also Suenaga (2011) for the discussion in detail.

Therefore, it can also be interpreted as follows: If seen from the 3rd layer, the change from ‘1-a’ to ‘1-b’ and the change from ‘2-a’ to ‘2-b’ will be the technological trajectory in the technological paradigm ‘3-b’. If seen from the 2nd layer, the change from ‘1-a’ to ‘1-b’ will be the technological trajectory in the technological paradigm ‘2-a’. If seen from the 1st layer, the change from the grown junction method to the alloy junction method will be the technological trajectory in the technological paradigm ‘1-b’. According to this interpretation, whether a specific change is an improvement along a technological trajectory or a shift in paradigm, with new technological trajectories emerging, depends on the layer from which it is seen. Moreover, although the scientific knowledge can also still be classified in detail, it will be enough just to clarify the existence of the hierarchy of scientific knowledge, or a technological paradigm, since the purpose here is to discuss essentials.

Of course, an old technological paradigm and a new technological paradigm may coexist. The vacuum tube and the semiconductor coexist, and the same may be said about the bipolar transistor and MOSFET. Moreover, science and technology affect each other mutually, and the chain (co-evolution) of science and technology forms an evolutionary system. For example, the invention of the point contact type transistor, based on the discovery of Walter H. Brattain and John Bardeen, led to William B. Shockley’s scientific knowledge about the junction type transistor, and the grown junction technology was based on Shockley’s scientific knowledge. Furthermore, the invention of MOSFET also led to advances in scientific knowledge about the quantum Hall effect by Klaus von Klitzing. That is, science provides the technological sources of a scientific question, technology also does so, and various feedback mechanisms exist between science and technology (also refer to Sect. 1.2).

Although we need to analyze the various examples, Yamaguchi’s analyses (2006, 2008, 2009) about the Industrial Revolution and other cases are extremely interesting.

For example, the Middle Eastern conflict affects the direction for seeking alternative energy sources. Although Dosi (1982, p. 156) mentions that ‘scope for substitution … is limited by the technology which itself defines the range of possible technological advances’, Yamaguchi’s model suggests that advances in scientific knowledge which generate new technological paradigms have an important role.

In this process, lock-in effects or path-dependency have an important influence.

About this phrase; see also Freeman and Perez (1988). ‘It is only when productivity along the old trajectories shows persistent limits to growth and future profits are seriously threatened that the high risks and costs of trying the new technologies appear as clearly justified’ (p. 49).

This is an important factor for long business fluctuations.

Refer also to Nonaka and Takeuchi (1995) in regard to the role of the ‘field’ in knowledge creation. They analyze the ‘field’ for changing tacit knowledge into explicit knowledge in the SECI model of knowledge creation.

See also Rosenberg (1990) in regard to this example. Rosenberg also discusses the relationship between scientific knowledge and technological knowledge in detail.

The reason the transistor was created in the Bell laboratory was that many specialists in various academic realms worked in the same field, transmitted tacit knowledge, and drew inspiration from each other. ‘All in all, the people playing a major role at one time or another in the work which led to the transistor discovery may have numbered about thirteen’ (Nelson 1962, p. 560).

For example, this argument is also related to arguments such as ‘More Moore’, ‘More than Moore’, and ‘Beyond CMOS’. Let me define ‘More Moore’ as ‘to pursue micro-fabrication on silicon CMOS’, ‘More than Moore’ as ‘to create new value through combinations of technology’, and ‘Beyond CMOS’ as ‘to bring forth new devices based on new connections or principles’. Although they do not necessarily correspond completely, it follows that ‘More Moore’ and ‘More than Moore’ represent paradigm-sustaining innovation. New devices based on new connections are paradigm-disruptive innovation in the first layer, and new devices based on new principles are paradigm-disruptive innovation in the second layer. Finally, paradigm disruptive innovation in the third layer is a device based on an academic framework, which is different to quantum mechanics (referred to here as ‘Beyond Quantum’).

See also the discussions about techno-economic paradigms and long waves, such as Freeman and Perez (1988).

See Chesbrough (2003) about open innovation.

This is related to the discussion about the relationship between diversity and innovation.

Suenaga (2012) examines the role of local government, focusing on IMEC in Belgium. In Japan, central government plays a significant role in implementation of science and technology policy and declines the degree of globalization about research and development in Japan. The example of IMEC has significant implications for Japan.