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Policy scenarios as an instrument for policymakers

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  • Wright, David
  • Stahl, Bernd
  • Hatzakis, Tally

Abstract

Scenarios are a methodology of futures and foresight research that has been established for more than half a century. Despite the rich literature on scenarios and ways of constructing them, the current scenario methodologies, current approaches to scenario constructions are often not well aligned with the needs of policymakers. Emerging technologies that are likely to achieve high social relevance in the short to mid-term future and that call for quick policy interventions are difficult to reflect using current scenario approaches. We have therefore developed a new type of scenario that we call a policy scenario. This paper develops the principles and justification for policy scenarios. We provide a detailed description of how they can be constructed, focusing on their key characteristics of policy requirements, plausibility, probability, credibility, expertise, objectivity and legitimacy. Following our stakeholder-based approach allows researchers to construct scenarios that are uniquely suited to inform policymakers and, in effect, the policy development process.

Suggested Citation

  • Wright, David & Stahl, Bernd & Hatzakis, Tally, 2020. "Policy scenarios as an instrument for policymakers," Technological Forecasting and Social Change, Elsevier, vol. 154(C).
    • Handle: RePEc:eee:tefoso:v:154:y:2020:i:c:s0040162519308753
    DOI: 10.1016/j.techfore.2020.119972
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    References listed on IDEAS

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    1. Lehoux, P. & Miller, F.A. & Williams-Jones, B., 2020. "Anticipatory governance and moral imagination: Methodological insights from a scenario-based public deliberation study," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    2. Goodpaster, Kenneth E., 1991. "Business Ethics and Stakeholder Analysis," Business Ethics Quarterly, Cambridge University Press, vol. 1(1), pages 53-73, January.
    3. Philippe Durance & Michel Godet, 2010. "Scenario building: Uses and abuses," Post-Print hal-02864615, HAL.
    4. Derbyshire, James, 2017. "Potential surprise theory as a theoretical foundation for scenario planning," Technological Forecasting and Social Change, Elsevier, vol. 124(C), pages 77-87.
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    Cited by:

    1. Chulok Alexander, 2021. "Applying blended foresight methods for revealing incentives and future strategies of key national innovation system players," Engineering Management in Production and Services, Sciendo, vol. 13(4), pages 160-173, December.
    2. Ehlers, Melf-Hinrich & Finger, Robert & El Benni, Nadja & Gocht, Alexander & Sørensen, Claus Aage Grøn & Gusset, Markus & Pfeifer, Catherine & Poppe, Krijn & Regan, Áine & Rose, David Christian & Wolf, 2022. "Scenarios for European agricultural policymaking in the era of digitalisation," Agricultural Systems, Elsevier, vol. 196(C).
    3. Stahl, B.C. & Andreou, A. & Brey, P. & Hatzakis, T. & Kirichenko, A. & Macnish, K. & Laulhé Shaelou, S. & Patel, A. & Ryan, M. & Wright, D., 2021. "Artificial intelligence for human flourishing – Beyond principles for machine learning," Journal of Business Research, Elsevier, vol. 124(C), pages 374-388.
    4. Douglas, Conor M.W. & Panagiotoglou, Dimitra & Dragojlovic, Nick & Lynd, Larry, 2021. "Methodology for constructing scenarios for health policy research: The case of coverage decision-making for drugs for rare diseases in Canada," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    5. Oughton,Edward J. & Comini,Niccolo & Foster,Vivien & Hall,Jim W., 2021. "Policy Choices Can Help Keep 4G and 5G Universal Broadband Affordable," Policy Research Working Paper Series 9563, The World Bank.
    6. Edward J Oughton & Niccol`o Comini & Vivien Foster & Jim W Hall, 2021. "Policy choices can help keep 4G and 5G universal broadband affordable," Papers 2101.07820, arXiv.org, revised Feb 2021.
    7. Stahl, Bernd Carsten & Brooks, Laurence & Hatzakis, Tally & Santiago, Nicole & Wright, David, 2023. "Exploring ethics and human rights in artificial intelligence – A Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    8. Amorim-Lopes, Mário & Oliveira, Mónica & Raposo, Mariana & Cardoso-Grilo, Teresa & Alvarenga, António & Barbas, Marta & Alves, Marco & Vieira, Ana & Barbosa-Póvoa, Ana, 2021. "Enhancing optimization planning models for health human resources management with foresight," Omega, Elsevier, vol. 103(C).
    9. Oughton, Edward J. & Comini, Niccolò & Foster, Vivien & Hall, Jim W., 2022. "Policy choices can help keep 4G and 5G universal broadband affordable," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    10. Pablo E. Carvajal & Asami Miketa & Nadeem Goussous & Pauline Fulcheri, 2022. "Best Practice in Government Use and Development of Long-Term Energy Transition Scenarios," Energies, MDPI, vol. 15(6), pages 1-21, March.
    11. Burt, George & Mackay, David & Mendibil, Kepa, 2021. "Overcoming multi-stakeholder fragmented narratives in land use, woodland and forestry policy: The role scenario planning and ‘dissociative jolts’," Technological Forecasting and Social Change, Elsevier, vol. 166(C).

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