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

Abstract

While the prospects for the world economy, especially advanced economies, are uncertain, and the fundamental solutions to important problems such as environmental problems have not yet been found, the emergence or development of new technological paradigms is expected. The emergence of technological paradigms is a most important phenomenon in economic development. In this paper, the relationship between science and technology will be classified using four diagrammatic models, and the hierarchy of technological paradigms and the characteristics of each hierarchy will be clarified in order to consider the emergence of these technological paradigms. In addition, this paper mentions the implications for the corporate strategy of R&D, science and technology policy, and economic theory.

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1 Introduction

While the prospects for the world economy, especially advanced economies, are uncertain, and the fundamental solutions to important problems such as environmental problems have not yet been found, the emergence or development of new ‘technological paradigms’ is expected. The concept of ‘technological paradigms’ was introduced by Dosi (1982), and has been a great influence on the development of evolutionary economics, etc. (e.g. see the special section of Industrial and Corporate Change, 2008, vol. 17 (3), “Technological Paradigms: Past, Present and Future”). Thirty years have passed since Dosi’s paper was published, but the potential of this concept is not exhausted. In the meantime, while science has been playing an increasingly important role in the emergence of technological paradigms, the so-called ‘new economics of science’ has accomplished surprising advances during the last several decades. However, the emergence of technological paradigms has not yet been clarified. Although Dosi (1982) discusses the economic, institutional, and social factors through which technological paradigms are selected from existing scientific knowledge, he does not fully consider the factor of the emergence of technological paradigms. It is necessary for economists, particularly neo-Schumpeterian and evolutionary economists, to pay attention to the factors and processes of the emergence of technological paradigms, which are very important in economic development. In this paper, the relationship between science and technology will be classified via some diagrammatic models, and will be further discussed. In particular, the paper focuses on the emergence of technological paradigms, and explores the factors and processes involved in this emergence. Moreover, it pays particular attention to the hierarchy of technological paradigms, clarifying the characteristics of each hierarchy, and considers the ways in which the paradigms have emerged, based on a diagrammatic model.

1.1 Differences Between Science and Technology

Science aims to provide an elucidation of natural phenomena, while the purpose of technology is to create artifacts. Moreover, scientific knowledge is much more codified than technological knowledge, and much technological knowledge is implicit in experience and skill (e.g. Dosi 1982). However, not all scientific knowledge is necessarily codified, and tacit knowledge, which cannot be codified, also plays an important role in many cases. Nevertheless, generally speaking, scientific knowledge is easier to spread compared to technological knowledge.

Advances in science build mainly on already existing scientific knowledge (scientific papers cite other scientific papers much more frequently than patents), while advances in technology build mainly on technological knowledge (e.g. patents cite other patents much more frequently than scientific papers) (Price 1965; Stokes 1997; Pavitt 1998).¹ Furthermore, academic institutions dominate advances in science, while business firms do so for advances in technology (e.g. Pavitt 1998).

One of the main purposes of academic research is to produce codified theories and models that explain and predict natural reality. To achieve analytical tractability, this requires simplification and reduction of the number of variables…. On the other hand, the main purpose of business research and development is to design and develop produceable and useful artefacts. These are often complex, involving numerous components, materials, performance constraints and interactions, and are therefore analytically intractable…. Knowledge is therefore accumulated through trial and error. As a consequence, the methodologies of ‘experiments’ in the two types of laboratories are often very different (Pavitt 1998, p. 795).

Scientists are concerned with the discovery and publication of new knowledge, but they are not concerned with its application. On the other hand, the concern of technologists or engineers is the practical application of knowledge and professional recognition, and not the publication of knowledge (Price 1965; Freeman and Soete 1997). Relatively speaking, scientists (or academic institutions) act with the aim of achieving social rewards, such as a reputation, rather than economic rewards, such as profit.² On the other hand, engineers (or businesses) act with the purpose of earning economic rewards rather than social rewards (Merton 1973; Dasgupta and David 1994; Pavitt 1998; Bach and Matt 2005; Yamaguchi 2006; Aghion et al. 2009).³

1.2 Relationship Between Science and Technology

Price (1965) argues that science and technology are two subsystems which develop autonomously, and he uses the metaphor of two dancing partners that have their own steps although dancing to the same music.⁴ Freeman and Soete (1997, p. 15) point out that this relationship between science and technology has changed since the nineteenth century, and sometimes they are ‘cheek to cheek’. That is, the relationship between science and technology has become much more intimate, and the professional industrial R&D department is the cause and consequence of this new intimacy. With respect to the relationship between science and technology, Brooks (1994) uses the metaphor of two strands of DNA which can exist independently, but cannot be truly functional until they are paired.

According to Rosenberg (1990), one of the reasons why some firms do basic research is to resolve practical problems and/or to exploit the first-mover advantage. Moreover, it is extremely difficult to distinguish between basic research and applied research, and the relationship between them is highly complex. As contributions which science gives to technology Brooks (1994) mentions: it provides a direct source of ideas, it is a source of tools and techniques, it aids development of new human skills, etc., and as contributions which technology gives to science: it is a fertile source of novel scientific questions, and a source of otherwise unavailable instrumentation and techniques.

Kuznets (1966) indicates the importance of applying science to economic production as the main characteristic of modern economic growth, but does not suggest that modern technological innovation is triggered by scientific discovery. Rosenberg (1982) also insists that technological knowledge has preceded scientific knowledge, and that, even in industries founded on scientific research, practical experience with the new technology often precedes scientific knowledge.

However, it is particularly important to mention that the relationship varies, subject to the stage of industrial development: the role of science is more important in the initial stage of industrial development. Dosi (1988) points out that scientific knowledge plays a crucial role in opening up new possibilities for major technological advances, and that in the twentieth century the emergence of major new technological paradigms has frequently been directly dependent on and directly linked with major scientific breakthroughs. However, although at least the first ten years of the history of the semiconductor industry were characterized by a crucial inter-relationship between science and technology, the distance between the two has increased since the 1960s. Basic semiconductor technology has become established and its development path no longer needs a direct ‘coupling’ with ‘Big Science’ (Dosi 1984, p. 28).

1.3 Diagrammatic Illustrations of the Relationship Between Science and Technology

Some studies have tried to express this relationship between science and technology in a diagram.⁵ Kline (1990) argues about the relationship between science and technology by using the ‘revised chain-linked model’. Kline points out that science contributes to innovation only in the KITS (Knowledge Interface of Technology and Science) of the revised chain-linked model; the research which is born from KITS is not as difficult as the research which is produced from scientific knowledge; the problems extracted from KITS are connected with advances in science and mathematics. Kline’s model demonstrates that scientific and technological knowledge are intertwined in the production process from the point of market discovery up to the point of sales.

Stokes (1997) also discusses the relationship between science and technology, based on ‘a revised dynamic model’. Existing understanding can bring about improved understanding through pure basic research, and existing technology can produce improved technology through purely applied research and development. Furthermore, science and technology are semiautonomous, and are only loosely coupled. However, they are at times strongly influenced by each other, with ‘use-inspired’ basic research often cast in the linking role. The use-inspired basic research is also known as ‘Pasteur’s quadrant’. Through use-inspired basic research, existing understanding can bring about improved understanding and/or technology, and existing technology can produce improved understanding and/or technology.⁶

Yamaguchi (2006, 2008) illustrates innovation processes in a two-dimensional diagram, an ‘innovation diagram’, plotting the concepts of ‘knowledge creation’ on a horizontal axis and the concepts of ‘knowledge realization’ on a vertical axis. According to him, ‘knowledge creation’ means to discover things which nobody knows, and the intellectual workings for the discovery are termed as ‘science’. On the contrary, ‘knowledge realization’ refers to intellectual workings to realize feasible things by collecting and integrating scientific and technological knowledge, and the intellectual workings are limited to workings of ‘technology’. In this diagram, science and technology are not a unified evolutionary system, but a chain of their actions forms an evolutionary system. In addition, in his diagram, science is located in ‘soil’, because it is not economically valued.

By using the concepts of technological paradigms and technological trajectories, Dosi (1982) argues about the processes by which technology is chosen from existing scientific knowledge.⁷ Cimoli and Dosi (1995) attempt to illustrate technological paradigms and technological trajectories by plotting two factors of production on vertical and horizontal axes. However, the relationship between science and technology is not illustrated in a model.

In Sect. 2, based on Yamaguchi’s innovation diagram which is partly amended, the relationship between science and technology is classified into four models. Suenaga (2011) clarified the hierarchy of technological paradigms and the characteristics of each soil layer, based on the analysis of Yamaguchi (2006) with regard to the transistor and MOSFET. However, the discussion is refined and the relationship between the four models and the emergences of technological paradigms are considered in Sects. 3 and 4 respectively to clarify. Finally, Sect. 5 concludes the article and points out some theoretical and political implications.

2 Diagrammatic Models of Science and Technology

This section discusses the relationship between science and technology based on a revised model of Yamaguchi’s innovation diagram. Yamaguchi’s model has not been developed in the neo-Schumpeterian tradition, and thus it could be further developed by utilizing neo-Schumpeterian research results.

Although he uses the concepts of ‘knowledge creation’ and ‘knowledge realization’, the intellectual workings for ‘knowledge creation’ are called ‘science’ and the intellectual workings for ‘knowledge realization’ are called ‘technology’, so that we use the terms, ‘science’ instead of ‘knowledge creation’, and ‘technology’ instead of ‘knowledge realization’.⁸

In this section, based on Yamaguchi’s innovation diagram, the relationship between science and technology is classified into four models. These are the Price model, which analyses the autonomy of science and technology, the Bush model, which focuses on science-driven technological progress, the Rosenberg model, which is based on technology-driven scientific progress, and the Dosi model, which considers the relationship between science and technology from the viewpoint of technological paradigms and trajectories.

2.1 Autonomy of Science and Technology

Figure 1 represents the case where science and technology autonomously develop. Existing scientific knowledge (S) advances through scientific research etc. (S → S′). Advances in scientific knowledge are indicated by a rightward arrow in soil because they are not valued economically. Existing technological knowledge (T) advances through technological development etc. (T → T′). This is illustrated as the upward arrow above the soil. Here, the case in which science and technology autonomously develop, as shown in Fig. 1, is referred to as the ‘Price model’, after Price (1965).

Fig. 1

Price model: a case in which science and technology autonomously develop. Note: Although this figure is described, based on the innovation diagram of Yamaguchi (2006), I~distinguish between existing scientific knowledge and technological knowledge

2.2 Science-Driven Technological Progress

Although science and technology develop autonomously, they are not completely independent. Regarding the relationship between science and technology, although Freeman and Soete (1997) describe it as ‘cheek to cheek’, and Brooks (1994) uses the metaphor of ‘two strands of DNA’, what is the actual relationship like in detail? Figure 2 illustrates the case in which advances in scientific knowledge (S → S′) bring about advances in technological knowledge (T). The circled numbers indicate the order of the relationship between science and technology. This relationship is generally called a linear model. In this paper, this model is called the ‘Bush model’, after Bush (1945), who is regarded as a representative advocate of the linear model.⁹

Fig. 2

Bush model (linear model): science → technology.Note: This figure expresses the characteristics of a linear model, based on Yamaguchi’s innovation diagram

2.3 Technology-Driven Scientific Progress

Figure 3 shows a case where existing technological knowledge triggers advances in scientific knowledge, and then scientific understanding encourages further advances in technology. As Rosenberg (1982) points out, technological knowledge without scientific understanding exists in many cases, and the existence of technological knowledge (T) promotes scientific understanding (S → S′). Furthermore, advanced scientific knowledge (S′) enforces advances in technological knowledge (T → T′). For example, although Duralumin was brought into existence by an engineer’s trial and error, the associated scientific understanding only came about much later. In addition, scientific understanding drives the advances in Duralumin technology (Rosenberg 1982). In this paper, this model is called the ‘Rosenberg model’.

Fig. 3

Rosenberg model: technology → science (→ technology). Note: This figure illustrates the view of Rosenberg (1982), based on Yamaguchi’s innovation diagram (2006)

2.4 Technological Paradigms and Trajectories

Dosi (1982) tries to capture the relationship between science and technology from the viewpoint of technological paradigms and trajectories. Figure 4 illustrates Dosi’s ‘technological paradigms’ and ‘technological trajectories’ (1982). With regard to Dosi’s (1982) definitions, this paper defines ‘technological paradigms’ as ‘a “model” and a “pattern” of a solution to selected technological problems, based on selected scientific knowledge’, and defines’ technological trajectories’ as’ the progressing process of technological knowledge, based on a technological paradigm’.¹⁰ Although Dosi, given the stock of scientific knowledge, discusses the process whereby technology is selected from existing scientific knowledge, scientific progress such as progress from S₁ to S₂ is illustrated in this figure. Advanced scientific knowledge, S₂, may induce new technological knowledge, T₂, such as the Bush model, or may be triggered by existing technological knowledge, T₂, according to the Rosenberg model. Therefore, Fig. 4 includes both the Bush model and the Rosenberg model. In Fig. 4, technological paradigms are expressed as a dotted line, and technological trajectories are illustrated as upward arrows within technological paradigms. The model which shows the relationship between science and technology, as shown in Fig. 4, is called the ‘Dosi model’ here.

Fig. 4

Dosi model: Technological paradigms and technological trajectories. Note: This figure illustrates the view of Dosi (1982), based on Yamaguchi’s innovation diagram (2006)

3 The Hierarchy of Technological Paradigms

The discussion in this section is based on the Dosi model, and considers the hierarchy of technological paradigms (Fig. 5). Although advances in scientific knowledge have been located in soil up to this point, there are various layers of soil. For example, in the process by which the semiconductor industry came into being and developed, while the academic framework itself changed from classical electromagnetics (3-a), the basis of tube technology, to quantum mechanics (3-b), the basis of semiconductor technology, there were also advances in science within the academic framework of quantum mechanics. For example, although the transformation of operating principles from current injection (2-a), the basis of bipolar transistor technology, to field effect (2-b), the basis of FET technology is based on the specific academic framework of quantum mechanics, it is less significant than the transformation of the academic framework. Moreover, the transformation of connection methods from point type (1-a) to junction type (1-b) is less significant than the transformation of the operating principles, because point and junction type are based on a specific operating principle, current injection. With regard to the diagram above, the transformation of the academic framework is described as being located in the deeper layer of soil (referred to here as the third layer), while the transformation of the operating principles is located in a middle layer of soil (referred to here as the second layer), and the transformation of the connection methods is located in a shallower layer of soil (referred to here as the first layer).¹¹

Fig. 5

Soil layers and hierarchy of technological paradigms

As already mentioned, the ‘technological paradigms’ in this paper are ‘a “model” and a “pattern” of a solution to selected technological problems, based on selected scientific knowledge’. This ‘selected scientific knowledge’ sometimes refers to the selected academic framework, such as quantum mechanics. However, it sometimes refers to the selected operating principles, such as current injection within the academic framework, and it sometimes refers to the selected connection methods, such as point type and junction type, within the operating principles such as current injection.

Advances in scientific knowledge in the third layer form more extensive technological paradigms (e.g. ‘3-b’), advances in scientific knowledge in the second layer form middle-sized technological paradigms (e.g. ‘2-a’, which is included in ‘3-b’), and advances in scientific knowledge in the first layer form smaller technological paradigms (e.g. ‘1-b’, which is included in ‘2-a’). As a result, layers are also formed in technological paradigms when a difference in the dimension (the depth of soil) of scientific knowledge exists.¹²

Table 1 sums up the characteristics of technological paradigms and scientific knowledge regarding the basis of each technological paradigm. Although Table 1 is drawn from the example of the transistor and MOSFET, the same argument can also be developed in other examples. That is, layers are formed in the soil, and the hierarchy of technological paradigms based on these layers is built, although the characteristics of each layer may differ.¹³ In this way, by clarifying the characteristics of the hierarchy of technological paradigms or soil layers, part of the method of producing new technological paradigms may become clear.

Table 1 Soil layers and technological paradigms/scientific knowledge

4 The Emergence of Technological Paradigms

How do new technological paradigms emerge? According to the Bush model (linear model), there are advances in scientific knowledge which have the possibility of producing a new technological paradigm. However, there are many cases where an advance in scientific knowledge does not produce a new technological paradigm. Moreover, there is a time-lag until advances in scientific knowledge produce new technological paradigms; sometimes this happens quickly (or almost immediately), and in other cases it takes a long time (tens of years or more than that). However, as there is much criticism about this, it is insufficient to just understand advances in scientific knowledge and new technological paradigms in terms of linear relationships (for example, Dosi 1982; Kline 1990; Stokes 1997; Nightingale 1998). Many economic factors affect advances in scientific knowledge, and the complexity and the uncertainty of the relationship between science and technology may be overlooked in the Bush model. In the Rosenberg model, the emergence of technological paradigms happens without scientific knowledge (understanding), and the solidity of technological paradigms increases with advances in scientific knowledge (understanding). Thus, the relationship between science and technology is not a one-way thing, and a chain of science and technology forms an evolutionary system, with science and technology having a mutual influence. Nevertheless, as time goes by, the importance not only of existing scientific knowledge but advances in scientific knowledge increases. In order to produce new technological paradigms which have great potential, advances in scientific knowledge are needed at deeper layers.

Dosi (1982) discusses the economic, institutional, and social factors through which technological paradigms are selected from existing scientific knowledge. For example, the marketability, potential profitability, and labor-saving capability of technological paradigms, and industrial and social conflict, have an influence on the process by which technological paradigms are selected.¹⁴ In this process, although the market plays a certain role, it is almost impossible to predict the long-term performance of technological paradigms. Therefore, it is not an approach like neoclassical economics (including endogenous economic growth theory) that is needed, but one like evolutionary economics (including Dosi et al.).¹⁵ Although it is necessary to generalize as regards the factors and process of the emergence of technological paradigms through various case studies, one might not be able to find anything like a general theory of the emergence of technological paradigms, as Cimoli and Dosi (1995, p. 254) point out.

Basically, if the possibility is high that technological trajectories will develop under a specific technological paradigm, the incentive to look for other technological paradigms decreases. On the other hand, if there is a low possibility that the technological trajectories will develop, the motivation to seek other technological paradigms increases.¹⁶ Moreover, if there is a high possibility that scientific knowledge will progress, the possibility that other technological paradigms can be selected increases. On the other hand, if the possibility is low that scientific knowledge will progress, the possibility that other technological paradigms can be selected decreases. The frequency of the emergence of technological paradigms increases as the layer becomes shallower, and the potential for new paradigms increases as the layer becomes deeper.¹⁷

What kind of corporate strategy or policy is needed in order to generate new technological paradigms? One important point in this regard is how to combine science and technology, since this combination plays an important role in creating new technological paradigms. Although science and technology have mutually independent characteristics, they are strongly influenced by each other. In a situation where new technological paradigms are needed, how both are combined becomes important. In particular, in order to create technological paradigms based on deeper layers, ‘a field’ which straddles between academics or between organizations may be needed.

Regarding this field, Yamaguchi (2009) suggests the concept of ‘a field of resonance’.¹⁸ According to him, the key to what new technological paradigm emerge depends on whether those who find the existential desire for ‘advances in scientific knowledge’ and ‘advances in technological knowledge’ can succeed in resonating this desire in a realistic place which can transmit tacit knowledge…Such a place is called the ‘field of resonance’.

Of course, there will be cases where those who have the existential desire for ‘advances in scientific knowledge’, and those who have the existential desire for ‘advances in technological knowledge’ are the same people,¹⁹ and cases where both are alive at completely different times and places. Nevertheless, as already mentioned, the importance of not only existing scientific knowledge but advances in scientific knowledge increases as time goes by, and the importance of sharing a ‘field’ where both can transmit tacit knowledge is increasing.²⁰

Table 2 generalizes the state of ‘a field of resonance’ to each soil layer of Table 1. According to the level (soil layer) at which the actor tries to create the technological paradigms, the person, organization, and scientific knowledge required for the field of resonance are different, although the state of optimal field of resonance changes with the characteristics of industry and the times. When considering the methods of research and development, or the policy of science and technology, it is important to recognize the hierarchy and characteristics in each such level.²¹

Table 2 Soil layers and field of resonance

5 Conclusions: Some Theoretical and Policy Implications

In Sect. 2, the relationship between science and technology is discussed in a number of models, based on Yamaguchi’s innovation diagram. The models are the Price model, which pays attention to the autonomy of science and technology, the Bush model, which focuses on science-driven technological progress, the Rosenberg model, which is based on technology-driven scientific progress, and the Dosi model, which considers the relationship between science and technology from the viewpoint of technological paradigms and trajectories. There are various ways of viewing this relationship, and we should discuss it from various points of view, taking into account economic development, corporate strategy, and S&T policy.

Section 3 focuses on the hierarchy of technological paradigms in order to describe the emergence of technological paradigms. Additionally, by clarifying the characteristics of each layer of technological paradigms and scientific knowledge, it proposes a conceptual framework to create technological paradigms. The scientific knowledge which is the foundation of technological paradigms consists of deeper layers forming the academic framework, and shallower layers forming the operating principles and connection methods. Furthermore, technological paradigms, which are based on the layer of scientific knowledge, exist hierarchically, and constitute a complex system. In order to come up with strategies and policies to create technological paradigms, we should make a structure of human and material resources and organizations considering the hierarchy of technological paradigms.

Although the integrated model of this paper is, in some respects, “impressionistic”, it is an interesting model which illustrates the evolutionary process of economic development. Although many economists, such as Kuznets (1966), have emphasized the role of science on economic development, we can explicitly consider the relationship between science and technology, and the one between technological paradigms and economic development, based on the integrated model. Though the relationship between science and technology is not uniform, a chain of science and technology forms technological paradigms, and the hierarchical development of technological paradigms results in industrial and economic development.

While traditional economic growth theory demonstrates the process of economic growth by plotting the capital stock per capita on a horizontal axis and the output per capita on a vertical axis, Cimoli and Dosi (1995) illustrates technological paradigms and technological trajectories by plotting two factors of production on vertical and horizontal axes. Although this paper considers the process of economic development by plotting science and technology on both axes, disregarding factors such as capital and labor, on which orthodox economics places significance, this is not wrong when discussing the long-term process of economic development. The essential factors in economic development are science and technology, rather than capital and labor which neoclassical economic growth theory focuses on. Moreover, the process of economic development is an evolutional process rather than an equilibrium process, and its process cannot be described using numerical formulae.

Nevertheless, this paper has a problem of theoretical imperfection. Simply speaking, scientists (or academic institutions) act with the aim of social rewards, and advances in science are a function of the input to scientific research. On the other hand, engineers (or business firms) act with a view to earning economic rewards, and advances in technology are a function of the input to technological development. Although science and technology develop autonomously, both are complexly intertwined, as already mentioned above. As a result, although it is difficult to be theoretically explicit about the totality of the relationship between the two, it is possible to theorize about the relationship, to some degree, by classifying some models, as in this paper.

The process by which science and technology form a chain in various ways, and the process through which technological paradigms are selected and developed, are just evolutionary processes. Technological paradigms which are not suited to the economic environment in the short term might be disregarded, even if they have long-term potential.

Moreover, although this research has elucidated the hierarchy of technological paradigms by clarifying the hierarchy of scientific knowledge, the existence of the hierarchy is a factor that brings short-, middle-, and long-term economic fluctuations.²² In addition, by clarifying the hierarchy of technological paradigms, the continuity and discontinuity of an industrial development can be discussed.

Schumpeter (1934, p. 66), in the explanation of new combinations, refers to the ‘introduction of a new method of production, that is one not yet tested by experience in the branch of manufacture concerned’, and states that it need by no means be founded upon a discovery that is scientifically new. Although he refers to a new method of production based on a discovery that is scientifically new as a new combination, the discovery in itself is not endogenous in his model. However, we have to endogenise ‘advances in science’ to theorize the essence of economic development, even if scientific knowledge precedes technological knowledge as in the Bush model, or technological knowledge precedes scientific knowledge as in the Rosenberg model.

Large central laboratories such as the Bell laboratory of AT&T used to play a significant role in the emergence of technological paradigms (in particular, based on deeper layers). However, because of the greater mobility of skilled researchers, the increased knowledge in society as a whole, and the development of venture capital, it is difficult for a central laboratory in a large company to create new technological paradigms (based on the third layer).²³ How companies efficiently produce new technological paradigms in an era of open innovation is an important topic for the collaboration of industry-academia management. Moreover, how science and technology are bound together is also a crucial problem from the viewpoint of the policy of science and technology.

According to the soil layer of technological paradigms which the organization aims to create, the proportion and level of human and material resources, the organization, and the scientific knowledge required for the field of resonance differ.²⁴ In particular, it is necessary to develop a management framework and policies for producing new technological paradigms based on the third layer. Many organizations all over the world are challenged with this difficulty, and then such case studies are a subject that should be studied further in the future.²⁵