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Integrating Delphi and participatory backcasting in pursuit of trustworthiness — The case of electric mobility in Germany

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  • Zimmermann, Martin
  • Darkow, Inga-Lena
  • von der Gracht, Heiko A.

Abstract

Backcasting is an established approach to assess the creation and realisation of desirable futures, being especially suitable for complex issues where a radical change is required. A variety of methods is used to execute backcasting exercises with broad stakeholder participation. However, due to certain group inefficiencies it is a challenge to execute backcasting exercises in a participatory and yet rigorous and trustworthy way. We present an innovative participatory backcasting approach, integrating a Delphi survey and semi-structured interviews for electric mobility in Germany. As a major contribution, we demonstrate how to increase trustworthiness in participatory backcasting, by allowing for continuous stakeholder participation in a structured and transparent manner: from the creation of a preferable future to the assessment of the major factors leading to this future. The results illustrate a future vision of electric mobility in Germany in the year 2030 and present a discussion of the major factors leading to this desirable future. In addition to presenting the major benefits of our approach by integrating Delphi and participatory backcasting, we also outline the challenges related to this approach, such as difficulties in developing detailed roadmaps or the limited inclusion of end-users as major stakeholders.

Suggested Citation

  • Zimmermann, Martin & Darkow, Inga-Lena & von der Gracht, Heiko A., 2012. "Integrating Delphi and participatory backcasting in pursuit of trustworthiness — The case of electric mobility in Germany," Technological Forecasting and Social Change, Elsevier, vol. 79(9), pages 1605-1621.
    • Handle: RePEc:eee:tefoso:v:79:y:2012:i:9:p:1605-1621
    DOI: 10.1016/j.techfore.2012.05.016
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    Cited by:

    1. Esmaelian, Majid & Tavana, Madjid & Di Caprio, Debora & Ansari, Reza, 2017. "A multiple correspondence analysis model for evaluating technology foresight methods," Technological Forecasting and Social Change, Elsevier, vol. 125(C), pages 188-205.
    2. Soria-Lara, Julio A. & Banister, David, 2017. "Participatory visioning in transport backcasting studies: Methodological lessons from Andalusia (Spain)," Journal of Transport Geography, Elsevier, vol. 58(C), pages 113-126.
    3. Kishita, Yusuke & McLellan, Benjamin C. & Giurco, Damien & Aoki, Kazumasu & Yoshizawa, Go & Handoh, Itsuki C., 2017. "Designing backcasting scenarios for resilient energy futures," Technological Forecasting and Social Change, Elsevier, vol. 124(C), pages 114-125.
    4. Can Bıyık, 2019. "Smart Cities in Turkey: Approaches, Advances and Applications with Greater Consideration for Future Urban Transport Development," Energies, MDPI, vol. 12(12), pages 1-33, June.
    5. Paul Timms & Miles Tight & David Watling, 2014. "Imagineering Mobility: Constructing Utopias for Future Urban Transport," Environment and Planning A, , vol. 46(1), pages 78-93, January.
    6. Pereverza, Kateryna & Pasichnyi, Oleksii & Kordas, Olga, 2019. "Modular participatory backcasting: A unifying framework for strategic planning in the heating sector," Energy Policy, Elsevier, vol. 124(C), pages 123-134.
    7. Ariza-Álvarez, Amor & Soria-Lara, Julio A. & Arce-Ruiz, Rosa M. & López-Lambas, María Eugenia & Jimenez-Espada, Montaña, 2021. "Experimenting with scenario-building narratives to integrate land use and transport," Transport Policy, Elsevier, vol. 101(C), pages 57-70.
    8. Kajikawa, Yuya & Mejia, Cristian & Wu, Mengjia & Zhang, Yi, 2022. "Academic landscape of Technological Forecasting and Social Change through citation network and topic analyses," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    9. Heiskanen, Aleksi & Hurmekoski, Elias & Toppinen, Anne & Näyhä, Annukka, 2022. "Exploring the unknowns – State of the art in qualitative forest-based sector foresight research," Forest Policy and Economics, Elsevier, vol. 135(C).
    10. 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.
    11. Toivonen, Ritva & Lilja, Anna & Vihemäki, Heini & Toppinen, Anne, 2021. "Future export markets of industrial wood construction – A qualitative backcasting study," Forest Policy and Economics, Elsevier, vol. 128(C).
    12. Khrisydel Rhea M. Supapo & Lorafe Lozano & Ian Dominic F. Tabañag & Edward M. Querikiol, 2022. "A Backcasting Analysis toward a 100% Renewable Energy Transition by 2040 for Off-Grid Islands," Energies, MDPI, vol. 15(13), pages 1-19, June.
    13. Sykes, Pete & Bell, Margaret & Dissanayake, Dilum, 2018. "Combined use of a backcast scenario and cross-impact matrix analysis to identify causes of uncertainty in a nascent transport infrastructure project," Transportation Research Part B: Methodological, Elsevier, vol. 116(C), pages 124-140.
    14. Kishita, Yusuke & Höjer, Mattias & Quist, Jaco, 2024. "Consolidating backcasting: A design framework towards a users’ guide," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    15. Helena Sustar & Miloš N. Mladenović & Moshe Givoni, 2020. "The Landscape of Envisioning and Speculative Design Methods for Sustainable Mobility Futures," Sustainability, MDPI, vol. 12(6), pages 1-24, March.
    16. Klenner, Philipp & Hüsig, Stefan & Dowling, Michael, 2013. "Ex-ante evaluation of disruptive susceptibility in established value networks—When are markets ready for disruptive innovations?," Research Policy, Elsevier, vol. 42(4), pages 914-927.
    17. Winkler, Jens & Moser, Roger, 2016. "Biases in future-oriented Delphi studies: A cognitive perspective," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 63-76.
    18. Barrios, Maite & Guilera, Georgina & Nuño, Laura & Gómez-Benito, Juana, 2021. "Consensus in the delphi method: What makes a decision change?," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    19. Sarkki, Simo & Pihlajamäki, Mia, 2019. "Baltic herring for food: Shades of grey in how backcasting recommendations work across exploratory scenarios," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 200-209.
    20. Soria-Lara, Julio A. & Ariza-Álvarez, Amor & Aguilera-Benavente, Francisco & Cascajo, Rocío & Arce-Ruiz, Rosa M. & López, Cristina & Gómez-Delgado, Montserrat, 2021. "Participatory visioning for building disruptive future scenarios for transport and land use planning," Journal of Transport Geography, Elsevier, vol. 90(C).
    21. Melander, Lisa & Dubois, Anna & Hedvall, Klas & Lind, Frida, 2019. "Future goods transport in Sweden 2050: Using a Delphi-based scenario analysis," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 178-189.
    22. Spickermann, Alexander & Zimmermann, Martin & von der Gracht, Heiko A., 2014. "Surface- and deep-level diversity in panel selection — Exploring diversity effects on response behaviour in foresight," Technological Forecasting and Social Change, Elsevier, vol. 85(C), pages 105-120.
    23. Spickermann, Alexander & Grienitz, Volker & von der Gracht, Heiko A., 2014. "Heading towards a multimodal city of the future?," Technological Forecasting and Social Change, Elsevier, vol. 89(C), pages 201-221.

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