Process of technical change

It is crucial to understand that the accumulation of knowledge via learning is inert unless it can be transcribed and transformed into a process (i.e. technical change) to realise its value. Firms in this regard seek to use knowledge in particular ways in order to maintain or enhance

their revenue or profits through technical change and competitive advantage, usually via increased efficiency and/or quality of their products and processes over that of their rivals in the marketplace. However, it is also important to understand that institutional and cultural settings and forms are likely to influence the way in which learning and knowledge accumulation processes occur and contribute towards the dynamic of uneven development in modern economies and industries. Whilst most economists (either implicitly or explicitly) view technical change as a critical component of long-term growth, their definitions and terminologies have often been mixed. Within a historical framework, Smith (1776), for example, viewed technical change as a by-product of the division of labour through which returns to scale were modified; Ricardo (1817) regarded it as fixed and unchanging; while Marx (1848) analysed technical change in terms of production and affects upon labour.

During the twentieth century, Schumpeter (1939, 1942) has commonly been credited as being one of the first economists to directly deal with the issue of technical change in a detailed manner, in contrast neo-classical economists viewed it as a relatively peripheral exogenous activity. The focus upon technical change was an incidental outcome of Schumpeter’s main interests, i.e. business cycles, entrepreneurship and capitalist evolution. There are two angles of view regarding Schumpeter and technical change (see Philips, 1971; Brouwer, 1991). The first is that of competitive capitalism, referred to as Mark 1, exemplified by ‘Business Cycles’ (1939), where the focus is upon entrepreneurship and endogenous technical change. The second is that of trustified capitalism, or Mark 2, encapsulated within ‘Capitalism, Socialism, and Democracy’ (1942) in which monopoly and exogenous technical change prevail. Differences between the two perspectives can be attributed to socio-economic structural change in the inter-war years.47

Unlike the perfect competition model presented in Schumpeter Mark 1, Mark 2 is identified with monopoly power, which, however, is not viewed as inherently detrimental to economic progress. Whereas from an orthodox economic viewpoint monopolies suppress competition, Schumpeter (1942) suggested that this was temporary and not absolute.48 Monopoly positions could be maintained only in the short-run, because the process of ‘creative’

destruction would inevitably replace or force monopolies to change. Contrary to stifling competition and progress, the process of attaining monopoly status actually facilitates technical change by providing temporary protection to enable firms to invest in research and development. The possibility of attaining such an advantage or the desire to maintain such a position provides important incentives for firms to keep ahead of rivals or new market entrants. Without such restrictions, firms would be reluctant to invest in risky or costly ventures out of fear that competitors or new entrants could or would be able to realise greater profits from their own individual endeavours. Thus technical change within Schumpeterian contexts is not seen as a cost-saving activity but rather as a way to earn monopoly profits. This enables the theory to break out of growth-accounting models of development.49

Schumpeter provides a useful context for the discussion of possible sources and ways in which technical change can arise, but his theory has not been found wholly satisfactory in terms of innovation or technical change. While Schumpeter distinguished between different types of technical change according to their total impact on entrepreneurial activity and output, he treated it as a homogenous process.50 In addition, he limited his focus on technical change by emphasising ways of re-combining capital (investment) and labour within a production function and equilibrium framework (Schumpeter, 1939, pp.62–63). Neo- Schumpeterians such as those associated with the Science Policy Research Unit at Sussex University in the 1970s and 1980s attempted to expand and formulate a more precise taxonomy. In particular, they attempted to differentiate between various types of technical change as a means of adding empirical substance to Schumpeter’s work (see Table 2.3). Neo-Schumpeterians have also sought to integrate ‘evolutionary’ economics, allowing them to counter the criticisms made by neo-classical economists by targeting the areas precisely where micro-economic models were the weakest, i.e. understanding and explaining the process of technical change.51

Table 2.3 Neo-Schumpeterian classifications of technical change. Source: Freeman and Perez, 1988, pp.45–47.

Technical change Description

Basic (radical) Related to major research and development (R&D) activity, which have significant (structural) effects upon the industry if changes are widely commercialised and adopted. The emergence of these forms of technical change is unevenly distributed (Mensch, 1979). In this context, Dosi (1988), for example, suggested that these forms (within certain time cycles) act as ‘springboards’ for economic growth.

Incremental (process) related

Change is continuous and adaptive in form; it is less revolutionary than basic (radical) forms of technical change. However, the process is more reactive to existing circumstance and does not determine structural shifts, but rather assists in the diffusion and accumulation of technical change across various levels of analysis.

Techno-economic paradigm shifts

Technological revolutions cause a dramatic upheaval in the economy, which 'may eventually embody a number of new technology systems. [It] not only leads to the emergence of a new range of products and services, systems and industries in its own right; it also affects directly or indirectly almost every other branch of the economy', i.e. it is a meta-paradigm (Freeman and Perez, 1988, p.47).

Technological system changes

These changes directly affect a number of industries and branches of the economy, both radically and incrementally. This aspect of technological system change is often associated with interrelated ‘constellations’; classic examples include the development of computers and the subsequent growth of the software industry.

For much of the post-war years Keynesian economics dominated, within this framework technical change was presumed to be incremental and continuous (Rosenberg, 1982). The Keynesian approach however had no solution for the emergence of stagflation, a term coined in the 1970s for the twin economic problems of stagnation (i.e. lagging or even negative growth) and inflation, these had not previously emerged together. As a result of this perceived problem economists, particularly those allied to Marxist perspectives, began to re-evaluate capitalist development, they went back to study long-wave growth theory and the work of Kondratieff and Schumpeter.52 While interest in long-wave theory in Britain and North America waned in the post-war era, it had nonetheless continued in Germany exemplified by the likes of Mensch (1971; 1972). One of the reasons as to why his work rose to prominence was that he not only evaluated past historical patterns but also sought to predict future change (Hall and Preston, 1988, p.17).

Mensch’s historical studies of economic evolution to a certain extent supported Schumpeter’s idea of innovations as emerging in fits and spurts. Mensch (1971; 1972) developed a

longitudinal model of industrial evolution and distinguished between ‘basic’ (which gives birth to new industries), ‘improved’ (in established industries), and ‘pseudo’ (when markets mature and there is the need for differentiation) forms of technical change. In his analysis of basic and improved innovation, Mensch demonstrated that social inventions and scientific discoveries support the emergence of improved technical change in a more or less continuous stream, whereas basic forms of technical change clustered in relatively short time periods. He also advanced the notion that these two forms of technical change activities compete with each other, largely because of inertia and the problem of scarce investment funds. Priorities fluctuate according to the economic climate. A key difference between Mensch and Schumpeter is centred upon vanishing investment opportunities to the market system as an entity, Mensch suggested that Schumpeter in rejecting this perspective:

managed to throw the baby out with the bathwater. Schumpeter (and many neo- Schumpeterian economists, for that matter) did not differentiate between industrial sectors and types of innovation. They therefore did not adequately consider the fact that this theory of dwindling investment opportunities provided the best explanation for the circumstances of structural instability and of partial growth in certain special areas (structural change on the micro- and mesolevel that would in effect stablize the macrosystem).

(Mensch, 1975, p.51)

Mensch incorporates the theory of vanishing investment opportunities allied to the product life cycle theory (as advanced by Vernon, 1966) to underpin changes in the frequency and utility of successive improvements or technical change in individual industries. This also provides a sequencing model for successive product and process innovations in certain industrial branches. In this way it depicts how a basic form of technical change unfolds and how it is followed by many genuine improvements during the industry’s time of prosperity, which in turn eventually gives way to a rising flood of pseudo-innovation in its stagnation phase. It is only when ‘mesoeconomic’ stagnation as referred to by Mensch appears in a number of industry related branches at the same time, this effect then surfaces within the macro-economic

environment and in society at large. When a number of industries reach stagnation simultaneously and there is a lack of basic innovation, technological ‘stalemate’ arises; this ends when new shoots allied to basic innovation emerge.

Mensch (1975) advanced the notion that technical stalemates underpinned recession, the way in which he went about compiling the relevant data for his theory however was criticised by the likes of Freeman et al. (1982). In particular, the method of selecting the actual date of the first introduction as the full birth of an innovation by Mensch caused neo-Schumpeterians to highlight this as a problem, additionally in selecting basic innovations and identifying clusters, the time periods involved also coincided with periods of recession. While Mensch believed that major depressions tended to trigger and accelerate innovation, Freeman and his colleagues contributed the emergence of innovation to quite different causes. These included advances in basic science and pressures leveraged by demand as well as technical causation links i.e. one innovation leading to another. Neo-Schumpeterians in general did not believe that severe depression or rapid inflation was conducive for major forms of innovation, especially when sales are depressed and the future looks grim. They instead had a strong attachment to Jacobs Schookler’s invention theory i.e. that high demand would stimulate research and development investment.

The role of investment in the innovation or technical change process is a key variable in how growth is derived; Perez (2002) for example highlights the process of techno-economic paradigm shift by focusing upon the role of financial capital. For each technological revolution, she suggests there are time lags within which there are strong divergences in the rates of growth associated with industries, regions and countries as well as worsening of income distribution trends. For example, the late 1990s and the ‘dotcom’ phenomenon, according to Perez caused significant frenzy within financial markets as a result of speculation, potential for significant financial gains and swindles. Such ‘bubbles’ also tended to end with crashes, recessions and depressions, later giving way, after a period of readjustment, to prosperity based upon the techno-economic paradigm shift. Perez following the neo-Schumpeterian

long-wave perspective suggests that such series of events occur fairly regularly about every half century, whilst economies seem to react to them in predictable ways.

In specifying the link between technology and finance, Perez details how after the introduction of new technologies (the installation period), financial capital contributes to the creation of speculative bubbles. This builds upon new technologies and contributes towards tensions and financial crises before structural change is implemented, and more homogenous growth emerges after a period of deployment or maturity. Thus two or three decades of turbulent adaptation and assimilation may elapse, from the moment that new technologies emerge, and when products, industries and infrastructures make their first impact to when the full fruits of the techno-economic paradigm shift becomes realisable. The role of financial capital becomes an essential part of the process of change. It supports development of new technologies in pursuit of profits; this consequently encourages speculation and investor frenzy in anticipation of great returns or fear of being left out of potential investment opportunities, such a process leads to the de-coupling of capital from the actual (life-cycle) value attached to new technologies. Links between the latter two variables are re-established after the financial ‘bubble’ crashes and socio-economic changes emerge, which stabilises uncertainties, this then provides the basis for the emergence of a new paradigm cycle.

Leaving aside long-wave theory and the investment cycle and returning to the process of technical change, two distinctive views as seen in Figure 2.9 can be established. The neo- classical model perceives technical change as a cost-reducing, resource- and profit- maximising variable, whilst an opposite stance is taken by evolutionary economics which focuses upon firm-specific judgement, comparative advantage, nominal income and demand. Studies such as that by Nelson and Winter (1982) have built on the evolutionary behavioural dynamics of firms and abandoned distinctions between factor substitution and shifts in the production function. Nelson and Winter attempt to provide a more realistic and descriptive characterisation of the process underpinning technical change by widening the long-term (micro and macro) economic implications of technical change by stressing the uncertain

nature of circumstance. Thus 'choice sets are not given and the consequences … are unknown' (Nelson and Winter, 1982, p.276).

Figure 2.9 Orthodox and evolutionary approaches to technical change.

A. Neo-classical approach Demand growth Price reductions Cost reductions Productivity increase Technical change development B. Evolutionary approach Demand growth Nominal income growth New/improved techniques or ideas Technical change development Comparative advantage

In contrast to neo-classical theory, which presupposes that enterprises are homogenous and have perfect knowledge or information, ‘evolutionary’ theory assumes the opposite, in that an unevenness of information and knowledge exists within the marketplace. In addition, enterprise behaviour and objectives, instead of being purely centred upon profit, are partly rational and partly obscure; this creates variation in terms of technical change outcome and opportunities.53 Importantly therefore:

This viewpoint gives the study of firm behaviour per se a very different status in evolutionary theory from the one that it has in orthodoxy. The more we can learn about the way in which firms actually behave, the more we will be able to understand the laws of evolutionary development governing larger systems that involve many interacting firms in particular selection environments.

(Nelson and Winter, 1982, p.276)

One of the central planks of evolutionary theory in relation to technical change behaviour is path dependency, which stresses the importance of micro-level historical events that structure future options or choices. Arthur (1989) was one of the first to model the importance of

increasing returns to scale as a source of technological lock-in. This added to the evolutionary perspective of technical change as a path-dependent variable, in the sense that it evolves from earlier accumulated knowledge. Since the initialisation points of technical change can differ substantially, especially in the context of information and knowledge transfer, the process can become incalculable and thus difficult to model. As a result of the multiple and often uncertain nature of the technical change trajectory, the evolutionary model has over the years lacked coherent structure as a productive source of empirical research and thus is not considered to be a workable theory. Although ‘evolutionary’ viewpoints have attempted to evaluate the process of technical change within a wider remit, criticism has centred upon the purely descriptive nature of the approach. For orthodox economists the output of such research is devoid of any useful numerical data that substantiate findings (Arrow, 1995).

The process of quantification can to a certain extent be pursued when technical change becomes visible and accessible via new or adapted forms of capital. For trades involving intangibles, however, it is a process that can be measured only indirectly. Besides the difficulty of identifying technical change, there is also the need to view the effect as a continuous process in relation to competitiveness rather than as a self-contained event, as has historically been the case with manufacturing. In this case, technical change within the framework of the ‘black-box’ has become better understood over the years, from the formalised and outdated scientific ‘linear’ model (Figure 2.10), towards the chain-linked overview of analysis (Figure 2.11).54 The latter approach is based upon an interactive perspective which follows on from the work of Usher (1980), by emphasising the development of knowledge (the core mechanism behind technical change) as a ‘cumulative synthesis’ of interaction between various actors, both internal and external to organisations, regional or national economies.

Figure 2.10 Linear technical change process. Source: Massey, Quintas and Wield, 1992, p.57.

Concept Activity Location Division of labour Outputs Fields

Basic research Applied research Experimental development Diffusion, transference

1. Research 1. Science 2. Development 2. Technology 3. Diffusion 3. Markets Private/ government or academic research laboratories

Industrial research and development laboratories

Factories and offices _{production/service units,} Factories, shops, markets

Scientists in laboratories, supported by technician

aides

Scientists, engineers in laboratories, engineers and technicians to design, build and

test prototypes

Production managers, craft workers, production line

workers

Scientific knowledge, ideas, research papers

Patents, scientific papers New products and

Figure 2.11 Chain-linked model of technical change. Source: Kline and Rosenberg, 1986, p. 290.

Chain-linked model showing flow paths of information and co-operation. Symbols on arrow:

C = central chain of innovation f = feedback loops

F = particularly important feedback.