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Predicting the future of disruptive technologies: The method of alternative histories

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  • Krotov, Vlad

Abstract

With digital technologies shaping competition in many industries, predicting the future of potentially disruptive technologies becomes an essential task of business leaders concerned with the survival and success of their organizations. Looking into the future of disruptive technologies requires a philosophical stance and a practical method that accommodates the inherent uncertainty and nonlinearity of the path of disruptive innovations. Unfortunately, much of the current thinking in relation to adoption and diffusion of innovations is rather linear and deterministic. This article proposes a set of philosophical principles, together with a practical brainstorming method, for glimpsing into the future of disruptive technologies. The method of alternative histories is based on the traditional brainstorming techniques and the philosophical ideas of Imre Lakatos, Roy Bhaskar, Bruno Latour, and Nassim Taleb.

Suggested Citation

  • Krotov, Vlad, 2019. "Predicting the future of disruptive technologies: The method of alternative histories," Business Horizons, Elsevier, vol. 62(6), pages 695-705.
    • Handle: RePEc:eee:bushor:v:62:y:2019:i:6:p:695-705
    DOI: 10.1016/j.bushor.2019.07.003
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    References listed on IDEAS

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    1. Kaplan, Andreas M. & Haenlein, Michael, 2010. "Users of the world, unite! The challenges and opportunities of Social Media," Business Horizons, Elsevier, vol. 53(1), pages 59-68, January.
    2. Krotov, Vlad, 2017. "The Internet of Things and new business opportunities," Business Horizons, Elsevier, vol. 60(6), pages 831-841.
    3. Kaplan, Andreas M. & Haenlein, Michael, 2016. "Higher education and the digital revolution: About MOOCs, SPOCs, social media, and the Cookie Monster," Business Horizons, Elsevier, vol. 59(4), pages 441-450.
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    Cited by:

    1. Minhao Xiang & Dian Fu & Kun Lv, 2023. "Identifying and Predicting Trends of Disruptive Technologies: An Empirical Study Based on Text Mining and Time Series Forecasting," Sustainability, MDPI, vol. 15(6), pages 1-22, March.
    2. Mario Coccia, 2020. "Cyclical phenomena in technological change," Papers 2010.03168, arXiv.org, revised Oct 2020.

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