تخریب خلاقانه مدل سازی:نفوذ فن آوری و تغییر ساختار صنعتی تا 2050

Future disruptive, pervasive technologies will have important consequences for industrial structure, economic growth and the environment. Drawing on theories of technological diffusion, industrial evolution and long-term technological change this paper explores the effect of the development and diffusion of two future pervasive technologies on five industrial sectors in three regions during the 21st century in terms of their effect on economic structural change. Through semi-structured interviews with over 100 experts in the two technologies, the paper quantifies the effects of future biotechnologies and nanotechnologies on the industrial structure of the EU, USA and China in 2020 and 2050. The paper finds that as a result of the development and diffusion of future biotechnologies and nanotechnologies, some industries grow whilst others decline and some new ones emerge. The evidence suggests that the effect is different across countries and time; whereas the experts commonly believe that effect of the technologies on the industrial structure of the EU and US is likely to be similar, the effect in China is considered to be less by 2020 but the same as in the EU and US by 2050. This finding has important implications for the location of production, economic growth and energy demand in the future.

Technological change, industrial sector change and global environmental change are intimately connected [1]. Over the last 250 years, five successive ‘techno-economic paradigms’, associated with a ‘cluster’ of inter-related radical and incremental innovations (product, process, technical, organisational and managerial) have had a pervasive effect throughout the whole economy [2] and [3]; facilitating increased production of more goods and services and influencing the level of aggregate energy demand (and methods of energy supply). The next 100 years will be no different and future disruptive, pervasive technologies will have important consequences for industrial structure, economic growth and the environment. From a neo-Schumpeterian standpoint, this paper builds on previous work [4], [5], [6] and [7] to demonstrate a method by which one can quantify the effect of technological change on industrial structure over the next century. Dewick et al. [4] and Miozzo et al. [5] describe the method by which one can consider the long-term effects of technological change on the environment and Kohler [6] and Pan [7] demonstrate how these concepts can be incorporated into a macro-economic model. Dewick et al. [4] described a methodology built on notions of ‘Kondratiev long waves’ and using an industrial classification based on technological characteristics [8] and [9]. The paper provided a qualitative assessment of the effects of biotechnologies, information technologies and nanotechnologies (the so-called BIN technologies) on four industries in the EU. The results suggested that the assimilation and effective use of the BIN technologies would have a significant effect on industrial structure, levels of production and energy demand to 2050. The main drawback of the paper is that the findings are qualitative and do not lend themselves to quantitative macro-econometric modelling. Also, given that technological diffusion is a global phenomenon, influenced by the movement of international capital, the operation of multinationals, etc., the consideration of the EU in isolation limits the implications one can draw from the study. Drawing on theories of international production from international business and innovation, Miozzo et al. [5] assess the impact of long-term technological change and changes in international production on the international division of labour and energy demand. By assessing two industrial sectors with different technological characteristics (the textile, clothing and footwear sector, and the chemical sector) Miozzo et al. examine the effects of the globalisation of production and of technological change in the two industries on the level of industrial production and resource intensity in different regions/countries over the last 30 years. The findings of the paper highlight the important role technological change has played in shaping the international division of labour and resource efficiency of industrial production since 1970. What Miozzo et al. [5] provide is a retrospective analysis of the effects of the development and diffusion of information technologies; they do not attempt to consider explicitly the future effects of biotechnologies or nanotechnologies. Again, the findings are qualitative and require further interpretation to be useful for a macro-econometric model. Kohler [6] develops a simulation model of long-term technical change. He argues that, due to deficiencies in data, the unsuitability of econometrics for modelling beyond the short-to-medium term as well as the number of socio-economic variables to be considered means that there is no generally accepted theory to date on long-term technical change for incorporation into a macro-modelling structure. Based on Freeman and Louca's [10] descriptive theory (see also [2] and [3]), which encompasses the ideas on long waves from Kondratiev and Schumpeter, Kohler argues that socio-economic activity since the late 1700s can be interpreted using a dynamic macroeconomic model. Learning by doing and falling production costs are combined with an investment bubble and a lagged supply response to generate the boom phase of a Kondratiev wave. The six phases of Freeman and Louca's [10] technology life cycle are reflected in S-curves, the slopes of which depend heavily on R&D investment in the technologies. Pan [7] describes in more detail how evolutionary economics notions of disequilibrium and technological change may be considered explicitly in terms of changes to the economic system using input–output modelling. He describes a method where biotechnologies drive the change in input–output structure based investments in R&D. This paper builds on earlier work to model the relationship between the evolution of industry and the diffusion of pervasive technologies to 2050 in three regions. We look at the effect of the development and diffusion of two future pervasive technologies – biotechnologies and nanotechnologies – expected to have widespread effects during the 21st century on five industrial sectors differentiated by their technological characteristics.1 The paper uses theories of technological diffusion to consider how developments in biotechnologies and nanotechnologies will affect the input–output composition of five industries: agriculture, health and education, chemicals, industrial machinery and distribution. The impact of the technologies is considered in three regions: Europe, the USA and China. Through semi-structured interviews with experts in biotechnologies and nanotechnologies, we consider the effects of technological change on the current input–output structure in the three regions and suggest what the coefficients (in value terms) will be at two future years – 2020 and 2050. The paper is structured as follows. Section 2 draws insights from the technological diffusion literature to assess how one can model the diffusion of generic technologies within and between countries. Section 3 describes the method for quantifying the effects of technological change on industrial structure in the three regions over the next 50 years. Section 4 presents the results of the method and provides a descriptive analysis of the results from the semi-structured interviews and Section 5 concludes by considering the consequences of the development and diffusion of biotechnologies and nanotechnologies for industrial structure, economic growth and energy demand.

The development and diffusion of biotechnologies and nanotechnologies will have important consequences for industrial structure, economic growth and energy demand. This paper has demonstrated a method by which one can quantify future industrial dynamics, based on notions of Kondratiev long-waves and the development and diffusion of generic technologies (i.e. pervasive technologies that manipulate organisms and materials), the nature of technological change in different industries and evolution in the location of industrial production. Particular theoretical attention has been placed on incorporating ideas of S-curves to map the diffusion of generic technologies across countries and over time. Expert opinion on changes in the input–output coefficients of a number of key industries allowed us to quantify the effects of technological diffusion across countries and over time. This paper provides quantitative results showing the effects of the development and diffusion of pervasive technologies on the current industrial structure in 2020 and 2050 in the EU, US and China. Within the analysis we note that as a result of future biotechnologies and nanotechnologies some industries grow (ceteris paribus; in terms of their output relative to other industries), whilst others decline and some new ones emerge. Generally speaking, the effect of the technologies on the industrial structure is considered by the experts to be similar in the EU and US; the effect in China is likely to be less by 2020 but the same as in the EU and US by 2050. Neo-classical modelling exercises using stable I–O coefficients (and therefore based on notions of equilibrium rather than disequilibrium) do not adequately reflect the central role of technological change in the evolution of industries. This paper contributes to the construction of disequilibrium, long-term macro-econometric model, within which technological change is considered explicitly in terms of its effect on economic structural change (see Barker et al. [49] for a description of early progress in the model's construction). The implications of the changes described in the paper await the completion of further modelling work; however, it is clear that policies to facilitate the diffusion of generic technologies such as biotechnologies and nanotechnologies will have important implications for a country's industrial structure and economic development. Based on changes in the input–output structure, knowledge of the widespread application of these technologies across different industries allows future modelling work to estimate how productivity may change as a result of technological change, with the associated implications for employment, consumption and trade. Future work will report the results of the modelling exercise, particularly with respect to whether the impacts of the technological change described will drive industrial structure and economic change in a sustainable direction in terms of energy demand and greenhouse gas emissions.