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Assessing socially disruptive technological change

Author

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  • Carlsen, H.
  • Dreborg, K.H.
  • Godman, M.
  • Hansson, S.O.
  • Johansson, L.
  • Wikman-Svahn, P.

Abstract

The co-evolution of society and potentially disruptive technologies makes decision guidance on such technologies difficult. Four basic principles are proposed for such decision guidance. None of the currently available methods satisfies these principles, but some of them contain useful methodological elements that should be integrated in a more satisfactory methodology. The outlines of such a methodology, multiple expertise interaction, are proposed. It combines elements from several previous methodologies, including (1) interdisciplinary groups of experts that assess the potential internal development of a particular technology; (2) external scenarios describing how the surrounding world can develop in ways that are relevant for the technology in question; and (3) a participatory process of convergence seminars, which is tailored to ensure that several alternative future developments are taken seriously into account. In particular, we suggest further development of a bottom-up scenario methodology to capture the co-evolutionary character of socio-technical development paths.

Suggested Citation

  • Carlsen, H. & Dreborg, K.H. & Godman, M. & Hansson, S.O. & Johansson, L. & Wikman-Svahn, P., 2010. "Assessing socially disruptive technological change," Technology in Society, Elsevier, vol. 32(3), pages 209-218.
    • Handle: RePEc:eee:teinso:v:32:y:2010:i:3:p:209-218
    DOI: 10.1016/j.techsoc.2010.07.002
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    References listed on IDEAS

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    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. He, Yubing & Lin, Ting & Zhang, Si, 2023. "Does complementary technology within an ecosystem affect disruptive innovation? Evidence from Chinese electric vehicle listed firms," Technology in Society, Elsevier, vol. 74(C).
    2. Üzelgün, Mehmet Ali & Pereira, João Rui, 2020. "Beyond the co-production of technology and society: The discursive treatment of technology with regard to near-term and long-term environmental goals," Technology in Society, Elsevier, vol. 61(C).
    3. Nilsson, David & Karpouzoglou, Timos & Wallin, Jörgen & Blomkvist, Pär & Golzar, Farzin & Martin, Viktoria, 2023. "Is on-property heat and greywater recovery a sustainable option? A quantitative and qualitative assessment up to 2050," Energy Policy, Elsevier, vol. 182(C).
    4. Carlsen, Henrik & Johansson, Linda & Wikman-Svahn, Per & Dreborg, Karl Henrik, 2014. "Co-evolutionary scenarios for creative prototyping of future robot systems for civil protection," Technological Forecasting and Social Change, Elsevier, vol. 84(C), pages 93-100.
    5. Katarzyna Halicka, 2020. "Technology Selection Using the TOPSIS Method," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 14(1), pages 85-96.
    6. Kwon, Heeyeul & Kim, Jieun & Park, Yongtae, 2017. "Applying LSA text mining technique in envisioning social impacts of emerging technologies: The case of drone technology," Technovation, Elsevier, vol. 60, pages 15-28.
    7. Dixon, Tim & Eames, Malcolm & Britnell, Judith & Watson, Georgia Butina & Hunt, Miriam, 2014. "Urban retrofitting: Identifying disruptive and sustaining technologies using performative and foresight techniques," Technological Forecasting and Social Change, Elsevier, vol. 89(C), pages 131-144.
    8. Hopster, Jeroen, 2021. "What are socially disruptive technologies?," Technology in Society, Elsevier, vol. 67(C).
    9. Al Lily, Abdulrahman Essa & Ismail, Abdelrahim Fathy & Abunasser, Fathi Mohammed & Alhajhoj Alqahtani, Rafdan Hassan, 2020. "Distance education as a response to pandemics: Coronavirus and Arab culture," Technology in Society, Elsevier, vol. 63(C).
    10. Amelung, Dorothee & Funke, Joachim, 2013. "Dealing with the uncertainties of climate engineering: Warnings from a psychological complex problem solving perspective," Technology in Society, Elsevier, vol. 35(1), pages 32-40.
    11. Weifeng Jia & Shuo Wang & Yongping Xie & Zifeng Chen & Kaixin Gong, 2022. "Disruptive technology identification of intelligent logistics robots in AIoT industry: Based on attributes and functions analysis," Systems Research and Behavioral Science, Wiley Blackwell, vol. 39(3), pages 557-568, May.

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