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Classification of Delphi outputs through robust ranking and fuzzy clustering for Delphi-based scenarios

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  • Di Zio, Simone
  • Bolzan, Mario
  • Marozzi, Marco

Abstract

This paper proposes a method for generating robust ranks of Delphi projections, which are particularly suitable as input for clustering algorithms. The resulting clusters can be used for the construction of Delphi-based scenarios. The method is very flexible and can be applied to the classification of any variable derived from subjective judgments. In the analysis and interpretation of the results of a Delphi, a series of problems emerge related to the use of the concept of distance. The use of robust ranks allows us to overcome these problems.

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  • Di Zio, Simone & Bolzan, Mario & Marozzi, Marco, 2021. "Classification of Delphi outputs through robust ranking and fuzzy clustering for Delphi-based scenarios," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    • Handle: RePEc:eee:tefoso:v:173:y:2021:i:c:s0040162521005734
    DOI: 10.1016/j.techfore.2021.121140
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    1. Peppel, Marcel & Ringbeck, Jürgen & Spinler, Stefan, 2022. "How will last-mile delivery be shaped in 2040? A Delphi-based scenario study," Technological Forecasting and Social Change, Elsevier, vol. 177(C).

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