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Framing Emerging Nanotechnologies: Steps Towards A Forward-Looking Analysis Of Skills

Author

Listed:
  • Konstantin Fursov

    () (National Research University Higher School of Economics, Institute for Statistical Studies and Economics of Knowledge, International Laboratory for Economics of Innovation Research Fellow)

  • Ian Miles

Abstract

How can we think about the implications of radical technological change for employment and skills? Given the long lead-times required to train professionals, this is an important question, and standard approaches to modeling employment and occupational trends only provide limited parts of the answer. Innovation studies provide us with some further tools for tackling the question, such as diffusion and industry life-cycle analysis, and ideas about different sorts of technological change (including technical paradigms, regimes, and trajectories of change), which are very relevant to emerging technologies like nanotechnology. There are many claims and much argument about the scope and speed of the evolution of nanotechnology. It poses particular challenges to conventional forecasting approaches precisely because it is difficult to resolve such debates in the infancy of a technology, and in this case knowledge is fragmented because of the intersection of numerous lines of development at the nano-scale. Current skill and employment projections for nanoindustries are problematic, so it is important to consider new ways to improve understanding and provide more policy-relevant intelligence.

Suggested Citation

  • Konstantin Fursov & Ian Miles, 2013. "Framing Emerging Nanotechnologies: Steps Towards A Forward-Looking Analysis Of Skills," HSE Working papers WP BRP 15/STI/2013, National Research University Higher School of Economics.
  • Handle: RePEc:hig:wpaper:wpbrp15sti2013
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    File URL: http://www.hse.ru/data/2013/07/24/1288648701/15STI2013.pdf
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    References listed on IDEAS

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    1. Dale W. Jorgenson & Mun S. Ho & Kevin J. Stiroh, 2008. "A Retrospective Look at the U.S. Productivity Growth Resurgence," Journal of Economic Perspectives, American Economic Association, vol. 22(1), pages 3-24, Winter.
    2. Ian Miles, 2010. "Nanotechnology Foresight: How Can We Explore Employment and Skills Implications?," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 4(1), pages 20-36.
    3. Freeman, Chris & Louca, Francisco, 2002. "As Time Goes By: From the Industrial Revolutions to the Information Revolution," OUP Catalogue, Oxford University Press, number 9780199251056.
    4. Christopher Palmberg, 2008. "The transfer and commercialisation of nanotechnology: a comparative analysis of university and company researchers," The Journal of Technology Transfer, Springer, vol. 33(6), pages 631-652, December.
    5. Natalia Shmatko, 2012. "Competences of Engineers. Evidence from a Comparative Study for Russia and EU Countries," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 6(4), pages 32-47.
    6. Leonid Gokhberg & Konstantin Fursov & Ian Miles & Giulio Perani, 2013. "Developing and using indicators of emerging and enabling technologies," Chapters,in: Handbook of Innovation Indicators and Measurement, chapter 15, pages 349-380 Edward Elgar Publishing.
    7. Natalia Shmatko, 2013. "Graduates’ Competencies For The Innovation Labour Market," HSE Working papers WP BRP 13/STI/2013, National Research University Higher School of Economics.
    8. Fred Gault, 2013. "Innovation indicators and measurement: an overview," Chapters,in: Handbook of Innovation Indicators and Measurement, chapter 1, pages 3-38 Edward Elgar Publishing.
    9. Evgeniy Kutsenko & Dirk Meissner, 2013. "Key Features Of The First Phase Of The National Cluster Program In Russia," HSE Working papers WP BRP 11/STI/2013, National Research University Higher School of Economics.
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    More about this item

    Keywords

    emerging technologies; nanotechnology; statistics; Foresight; skills;

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Z13 - Other Special Topics - - Cultural Economics - - - Economic Sociology; Economic Anthropology; Language; Social and Economic Stratification

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