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A disruption framework

Author

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  • Kilkki, Kalevi
  • Mäntylä, Martti
  • Karhu, Kimmo
  • Hämmäinen, Heikki
  • Ailisto, Heikki
Abstract
One of the fundamental dilemmas of modern society is the unpredictable and problematic effect of rapid technological development. Sometimes the consequences are momentous not only on the level of a firm, but also on the level of an entire industry or society. This paper provides a framework to understand and assess such disruptions with a focus on the firm and industry levels. First, we give a generally applicable definition for a disruption as an event in which an agent must redesign its strategy to survive a change in the environment. Then we construct a layered model that spans from basic science to society and enables a systematic analysis of different types of disruption. The model also helps in analyzing the spread of innovations both vertically between layers and horizontally between industries. Thirdly, we introduce three main threats that may lead to a disruption and four basic strategies applicable when a disruption occurs. Finally, the framework is used to study four cases: GSM, GPS, the digitalization of photography, and 3D printing. The main contribution of this paper is the simple yet expressive model for understanding and analyzing the spread of industry-level disruptions through several layers and between industries.

Suggested Citation

  • Kilkki, Kalevi & Mäntylä, Martti & Karhu, Kimmo & Hämmäinen, Heikki & Ailisto, Heikki, 2018. "A disruption framework," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 275-284.
    • Handle: RePEc:eee:tefoso:v:129:y:2018:i:c:p:275-284
    DOI: 10.1016/j.techfore.2017.09.034
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    References listed on IDEAS

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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. Langley, Paul & Rieple, Alison, 2021. "Incumbents’ capabilities to win in a digitised world: The case of the fashion industry," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    3. To, Chester K.M. & Chau, K.P. & Kan, Chi Wai, 2020. "The logic of innovative value proposition: A schema for characterizing and predicting business model evolution," Journal of Business Research, Elsevier, vol. 112(C), pages 502-520.
    4. Mario Coccia, 2020. "Cyclical phenomena in technological change," Papers 2010.03168, arXiv.org, revised Oct 2020.
    5. Carlos Ferreira & Alessandro Merendino & Maureen Meadows, 2023. "Disruption and Legitimacy: Big Data in Society," Information Systems Frontiers, Springer, vol. 25(3), pages 1081-1100, June.
    6. Shi, Xianwei & Liang, Xingkun & Luo, Yining, 2023. "Unpacking the intellectual structure of ecosystem research in innovation studies," Research Policy, Elsevier, vol. 52(6).
    7. Vesselkov, Alexandr & Hämmäinen, Heikki & Töyli, Juuso, 2018. "Technology and value network evolution in telehealth," Technological Forecasting and Social Change, Elsevier, vol. 134(C), pages 207-222.
    8. Hopster, Jeroen, 2021. "What are socially disruptive technologies?," Technology in Society, Elsevier, vol. 67(C).
    9. Brougham, David & Haar, Jarrod, 2020. "Technological disruption and employment: The influence on job insecurity and turnover intentions: A multi-country study," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    10. Ben-Slimane, Karim & Diridollou, Cédric & Hamadache, Karim, 2020. "The legitimation strategies of early stage disruptive innovation," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    11. Rijswijk, Kelly & de Vries, Jasper R. & Klerkx, Laurens & Turner, James A., 2023. "The enabling and constraining connections between trust and digitalisation in incumbent value chains," Technological Forecasting and Social Change, Elsevier, vol. 186(PA).
    12. Trabucchi, Daniel & Talenti, Luca & Buganza, Tommaso, 2019. "How do Big Bang Disruptors look like? A Business Model perspective," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 330-340.
    13. Blume, Maximilian & Oberländer, Anna Maria & Röglinger, Maximilian & Rosemann, Michael & Wyrtki, Katrin, 2020. "Ex ante assessment of disruptive threats: Identifying relevant threats before one is disrupted," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    14. Marić, Josip & Opazo-Basáez, Marco & Vlačić, Božidar & Dabić, Marina, 2023. "Innovation management of three-dimensional printing (3DP) technology: Disclosing insights from existing literature and determining future research streams," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    15. Uzuegbunam, Ikenna & Geringer, J. Michael, 2021. "Culture, connectedness, and international adoption of disruptive innovation," Journal of International Management, Elsevier, vol. 27(1).
    16. Julian Marius Müller & Raphael Kunderer, 2019. "Ex-Ante Prediction of Disruptive Innovation: The Case of Battery Technologies," Sustainability, MDPI, vol. 11(19), pages 1-19, September.
    17. Rouse, Marybeth & Batiz-Lazo, Bernardo & Carbo Valverde, Santiago, 2020. "All about the state-Fifty years of innovative technology to deliver an inclusive financial sector," MPRA Paper 102159, University Library of Munich, Germany.
    18. Xiwen Liu & Xuezhao Wang & Lucheng Lyu & Yanpeng Wang, 2022. "Identifying disruptive technologies by integrating multi-source data," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5325-5351, September.

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