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Surface- and deep-level diversity in panel selection — Exploring diversity effects on response behaviour in foresight

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  • Spickermann, Alexander
  • Zimmermann, Martin
  • von der Gracht, Heiko A.

Abstract

In addition to foresight research endeavours that focus on the application of the Delphi survey technique, numerous research articles have dealt with the method itself: namely improving the Delphi technique's task and process characteristics. Particularly in Policy Delphi surveys and related variations that strive to explore opposing views, the diversity of the Delphi panel has been scrutinised. In the majority of earlier Policy Delphi studies, expertise accounted for the most predominant panel selection criterion. However, further surface- and deep-level diversity dimensions discussed in related social science research need to be incorporated for steering diversity in panel selection. In this article, the main effects of surface- and deep-level panel diversity on response behaviour are examined, focussing on extreme response style (ERS). Moreover, interaction phenomena of diversity variables are considered. By conducting a Policy Delphi in real-time format on the future of multimodal mobility, we demonstrate that value attributes significantly influence extreme response behaviour while expertise is especially important in combination with various other diversity variables. Furthermore, we identified a moderating effect of age on the relationship between environmental value characteristics and Delphi panellists' response behaviour.

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  • 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.
    • Handle: RePEc:eee:tefoso:v:85:y:2014:i:c:p:105-120
    DOI: 10.1016/j.techfore.2013.04.009
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    Cited by:

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    4. Frevel, Nicolas & Beiderbeck, Daniel & Schmidt, Sascha L., 2022. "The impact of technology on sports – A prospective study," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    5. Büchel, Hendrik & Spinler, Stefan, 2024. "The impact of the metaverse on e-commerce business models – A delphi-based scenario study," Technology in Society, Elsevier, vol. 76(C).
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    7. Roßmann, Bernhard & Canzaniello, Angelo & von der Gracht, Heiko & Hartmann, Evi, 2018. "The future and social impact of Big Data Analytics in Supply Chain Management: Results from a Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 135-149.
    8. Heiko A. von der Gracht, 2022. "The force that rules the world: Commentary on Fenton‐O'Creevy and Tuckett (2021)," Futures & Foresight Science, John Wiley & Sons, vol. 4(3-4), September.
    9. Makkonen, Marika & Hujala, Teppo & Uusivuori, Jussi, 2016. "Policy experts' propensity to change their opinion along Delphi rounds," Technological Forecasting and Social Change, Elsevier, vol. 109(C), pages 61-68.
    10. Geissler, Dominik & Beiderbeck, Daniel & Schmidt, Sascha L. & Schreyer, Dominik, 2024. "Emerging technologies and shifting consumer motives: Projecting the future of the top-tier sports media product," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    11. Gebhardt, Maximilian & Spieske, Alexander & Birkel, Hendrik, 2022. "The future of the circular economy and its effect on supply chain dependencies: Empirical evidence from a Delphi study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    12. Tiberius, Victor & Gojowy, Robin & Dabić, Marina, 2022. "Forecasting the future of robo advisory: A three-stage Delphi study on economic, technological, and societal implications," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    13. von Briel, Frederik, 2018. "The future of omnichannel retail: A four-stage Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 217-229.
    14. Beiderbeck, Daniel & Evans, Nicolas & Frevel, Nicolas & Schmidt, Sascha L., 2023. "The impact of technology on the future of football – A global Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    15. Belton, Ian & MacDonald, Alice & Wright, George & Hamlin, Iain, 2019. "Improving the practical application of the Delphi method in group-based judgment: A six-step prescription for a well-founded and defensible process," Technological Forecasting and Social Change, Elsevier, vol. 147(C), pages 72-82.
    16. Corinne Post & Daniel Muzio & Riikka Sarala & Liqun Wei & Dries Faems, 2021. "Theorizing Diversity in Management Studies: New Perspectives and Future Directions," Journal of Management Studies, Wiley Blackwell, vol. 58(8), pages 2003-2023, December.
    17. Bathke, Henrik & Hartmann, Evi, 2021. "Accepting a crowdsourced delivery - A choice-based conjoint analysis," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Adapting to the Future: Maritime and City Logistics in the Context of Digitalization and Sustainability. Proceedings of the Hamburg International Conf, volume 32, pages 65-95, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    18. Fritschy, Carolin & Spinler, Stefan, 2019. "The impact of autonomous trucks on business models in the automotive and logistics industry–a Delphi-based scenario study," Technological Forecasting and Social Change, Elsevier, vol. 148(C).

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