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Forecasting the Technology Revolution: Results and learnings from the TechCast Project

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  • Halal, William E.

Abstract

This research report presents latest results on the TechCast Project, first reported in Technology Forecasting & Social Change 14years ago [1]. TechCast is an online Delphi system that pools background trends and the judgment of experts around the world to forecast breakthroughs in all fields. Results are presented for strategic technological advances that are likely to enter the mainstream and their expected impacts, providing an overview of the Technology Revolution. Aggregating the forecast data then provides macro-forecasts of broad timetables for economic and social change. This analysis suggests that the global economy is likely to enter a new economic upcycle about 2015 and reach an advanced stage of development about 2020. We also examine examples of how organizations develop technology strategy to compete in an era of economic transformation, and conclude by analyzing the role of forecasting as one of many methods for reducing uncertainty.

Suggested Citation

  • Halal, William E., 2013. "Forecasting the Technology Revolution: Results and learnings from the TechCast Project," Technological Forecasting and Social Change, Elsevier, vol. 80(8), pages 1635-1643.
    • Handle: RePEc:eee:tefoso:v:80:y:2013:i:8:p:1635-1643
    DOI: 10.1016/j.techfore.2013.02.008
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    Cited by:

    1. Undheim, Trond Arne, 2024. "In search of better methods for the longitudinal assessment of tech-derived X-risks: How five leading scenario planning efforts can help," Technology in Society, Elsevier, vol. 77(C).
    2. Martinez, John & Phillips, Fred & Walsh, Steve, 2023. "The Journal that Hal Built: TF&SC's founding editor and early authors laid foundations for a discipline and a premier journal," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    3. Azagra-Caro, Joaquín M. & Tijssen, Robert J.W. & Tur, Elena M. & Yegros-Yegros, Alfredo, 2019. "University-industry scientific production and the Great Recession," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 210-220.
    4. Marcin Kozak & Olesia Iefremova, 2014. "Implementation Of The Delphi Technique In Finance," "e-Finanse", University of Information Technology and Management, Institute of Financial Research and Analysis, vol. 10(4), pages 36-45, May.
    5. Förster, Bernadette, 2015. "Technology foresight for sustainable production in the German automotive supplier industry," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 237-248.
    6. Kott, Alexander & Perconti, Philip, 2018. "Long-term forecasts of military technologies for a 20–30 year horizon: An empirical assessment of accuracy," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 272-279.
    7. Julia V. Ponomareva & Anna V. Sokolova, 2015. "The Identification of Weak Signals and Wild Cards in Foresight Methodology: Stages and Methods," HSE Working papers WP BRP 46/STI/2015, National Research University Higher School of Economics.

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