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Towards improving the relevance of scenarios for public policy questions: A proposed methodological framework for policy relevant low carbon scenarios

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  • Hughes, Nick

Abstract

A previous review of the use of scenarios in public policy found that the evidence for their impact on policy making was limited. One of the reasons suggested for this lack of policy impact was the disconnection between the time scales explored in long range scenarios, and those typical of the perspective of the policy maker. This paper argues that scenarios can have a valuable role in connecting long term policy goals to their implications for near term decisions. Key to the effectiveness of public policy scenarios in this regard is an actor-based view of the system, which connects long term pathways to the implications of near-term actor decisions. The paper focusses on developing a methodological framework for low carbon scenarios., Reviewing scenario literature, it identifies ‘trend based’, ‘actor based’ and ‘technical feasibility’ scenario approaches, and argues that the insights derived from each of these modes of analysis is important to consider in low carbon scenarios. Moreover, the iteration between these levels as the scenario moves through time is equally important. The paper therefore proposes a 3 level methodological framework as a basis for constructing low carbon scenarios with high policy tractability.

Suggested Citation

  • Hughes, Nick, 2013. "Towards improving the relevance of scenarios for public policy questions: A proposed methodological framework for policy relevant low carbon scenarios," Technological Forecasting and Social Change, Elsevier, vol. 80(4), pages 687-698.
  • Handle: RePEc:eee:tefoso:v:80:y:2013:i:4:p:687-698
    DOI: 10.1016/j.techfore.2012.07.009
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    Citations

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    Cited by:

    1. Andersen, Per Dannemand & Hansen, Meiken & Selin, Cynthia, 2021. "Stakeholder inclusion in scenario planning—A review of European projects," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    2. Addolorata Marasco & Alessandro Romano, 2018. "Deterministic modeling in scenario forecasting: estimating the effects of two public policies on intergenerational conflict," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(5), pages 2345-2371, September.
    3. Minkkinen, Matti, 2019. "The anatomy of plausible futures in policy processes: Comparing the cases of data protection and comprehensive security," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 172-180.
    4. DeCarolis, Joseph & Daly, Hannah & Dodds, Paul & Keppo, Ilkka & Li, Francis & McDowall, Will & Pye, Steve & Strachan, Neil & Trutnevyte, Evelina & Usher, Will & Winning, Matthew & Yeh, Sonia & Zeyring, 2017. "Formalizing best practice for energy system optimization modelling," Applied Energy, Elsevier, vol. 194(C), pages 184-198.
    5. Cairns, George & Wright, George & Fairbrother, Peter, 2016. "Promoting articulated action from diverse stakeholders in response to public policy scenarios: A case analysis of the use of ‘scenario improvisation’ method," Technological Forecasting and Social Change, Elsevier, vol. 103(C), pages 97-108.
    6. Skea, Jim & van Diemen, Renée & Portugal-Pereira, Joana & Khourdajie, Alaa Al, 2021. "Outlooks, explorations and normative scenarios: Approaches to global energy futures compared," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    7. Nilsson, Måns & Nykvist, Björn, 2016. "Governing the electric vehicle transition – Near term interventions to support a green energy economy," Applied Energy, Elsevier, vol. 179(C), pages 1360-1371.
    8. Cairns, George & Wright, George & Fairbrother, Peter & Phillips, Richard, 2017. "‘Branching scenarios’ seeking articulated action for regional regeneration – A case study of limited success," Technological Forecasting and Social Change, Elsevier, vol. 124(C), pages 189-202.
    9. 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).
    10. Minkkinen, Matti & Auffermann, Burkhard & Ahokas, Ira, 2019. "Six foresight frames: Classifying policy foresight processes in foresight systems according to perceived unpredictability and pursued change," Technological Forecasting and Social Change, Elsevier, vol. 149(C).
    11. Chen, Jiandong & Gao, Ming & Mangla, Sachin Kumar & Song, Malin & Wen, Jie, 2020. "Effects of technological changes on China's carbon emissions," Technological Forecasting and Social Change, Elsevier, vol. 153(C).
    12. Derbyshire, James & Wright, George, 2017. "Augmenting the intuitive logics scenario planning method for a more comprehensive analysis of causation," International Journal of Forecasting, Elsevier, vol. 33(1), pages 254-266.
    13. Zhuo Hu & Dong Huang & Congjun Rao & Xiaolin Xu, 2016. "Innovative allocation mechanism design of carbon emission permits in China under the background of a low-carbon economy," Environment and Planning B, , vol. 43(2), pages 419-434, March.
    14. Watson, Jim & Gross, Rob & Ketsopoulou, Ioanna & Winskel, Mark, 2015. "The impact of uncertainties on the UK's medium-term climate change targets," Energy Policy, Elsevier, vol. 87(C), pages 685-695.
    15. Hooper, Tara & Austen, Melanie C. & Beaumont, Nicola & Heptonstall, Philip & Holland, Robert A. & Ketsopoulou, Ioanna & Taylor, Gail & Watson, Jim & Winskel, Mark, 2018. "Do energy scenarios pay sufficient attention to the environment? Lessons from the UK to support improved policy outcomes," Energy Policy, Elsevier, vol. 115(C), pages 397-408.
    16. MacKay, R. Bradley & Stoyanova, Veselina, 2017. "Scenario planning with a sociological eye: Augmenting the intuitive logics approach to understanding the Future of Scotland and the UK," Technological Forecasting and Social Change, Elsevier, vol. 124(C), pages 88-100.
    17. Turnheim, Bruno & Nykvist, Björn, 2019. "Opening up the feasibility of sustainability transitions pathways (STPs): Representations, potentials, and conditions," Research Policy, Elsevier, vol. 48(3), pages 775-788.
    18. Trutnevyte, Evelina & Barton, John & O'Grady, Áine & Ogunkunle, Damiete & Pudjianto, Danny & Robertson, Elizabeth, 2014. "Linking a storyline with multiple models: A cross-scale study of the UK power system transition," Technological Forecasting and Social Change, Elsevier, vol. 89(C), pages 26-42.
    19. Ramboarison-Lalao, Lovanirina & Gannouni, Kais, 2019. "Liberated firm, a leverage of well-being and technological change? A prospective study based on the scenario method," Technological Forecasting and Social Change, Elsevier, vol. 140(C), pages 129-139.
    20. Alexandros Flamos, 2016. "A Sectoral Micro-Economic Approach to Scenario Selection and Development: The Case of the Greek Power Sector," Energies, MDPI, vol. 9(2), pages 1-12, January.
    21. Su, Chi-Wei & Yuan, Xi & Tao, Ran & Shao, Xuefeng, 2022. "Time and frequency domain connectedness analysis of the energy transformation under climate policy," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    22. Geels, F.W. & McMeekin, A. & Pfluger, B., 2020. "Socio-technical scenarios as a methodological tool to explore social and political feasibility in low-carbon transitions: Bridging computer models and the multi-level perspective in UK electricity gen," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    23. Hussain, M. & Tapinos, E. & Knight, L., 2017. "Scenario-driven roadmapping for technology foresight," Technological Forecasting and Social Change, Elsevier, vol. 124(C), pages 160-177.
    24. Zhu, Lin & Cunningham, Scott W., 2022. "Unveiling the knowledge structure of technological forecasting and social change (1969–2020) through an NMF-based hierarchical topic model," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    25. Derbyshire, James & Giovannetti, Emanuele, 2017. "Understanding the failure to understand New Product Development failures: Mitigating the uncertainty associated with innovating new products by combining scenario planning and forecasting," Technological Forecasting and Social Change, Elsevier, vol. 125(C), pages 334-344.

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