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Real Time Spatial Delphi: Fast convergence of experts' opinions on the territory

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  • Di Zio, Simone
  • Castillo Rosas, Juan Daniel
  • Lamelza, Luana

Abstract

Considering the advantages of the online consultation methodologies and the potential of WebGIS technology, we introduce a novel real-time Delphi technique, which exploits the features of two existing methods: Real Time Delphi and Spatial Delphi. This new technique, called Real Time Spatial Delphi, preserves most of the advantages of both methods, minimizes the disadvantages, and develops new potential. A panel of experts, suitably chosen according to the application, answers a geo-questionnaire by placing points on an online interactive map and presenting written arguments. The system automatically calculates and displays a circle representing the convergence of the opinions, which shrinks and moves in real-time. The final result is the delimitation of an area most suitable for a given action or for the occurrence of a future event and is immediately usable for decision support and/or spatial scenario building without any processing. We applied this technique to the zoning of street prostitution in Italy and identified several areas inside five municipalities where the zoning was considered most appropriate by the experts. This new Delphi method represents an innovative way of eliciting experts' opinions regarding a simple and intuitive platform, which is potentially applicable to a very broad spectrum of forecast/decision making issues.

Suggested Citation

  • Di Zio, Simone & Castillo Rosas, Juan Daniel & Lamelza, Luana, 2017. "Real Time Spatial Delphi: Fast convergence of experts' opinions on the territory," Technological Forecasting and Social Change, Elsevier, vol. 115(C), pages 143-154.
    • Handle: RePEc:eee:tefoso:v:115:y:2017:i:c:p:143-154
    DOI: 10.1016/j.techfore.2016.09.029
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    References listed on IDEAS

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    1. Di Zio, Simone & Staniscia, Barbara, 2014. "A Spatial version of the Shang method," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 207-215.
    2. Norman Dalkey & Olaf Helmer, 1963. "An Experimental Application of the DELPHI Method to the Use of Experts," Management Science, INFORMS, vol. 9(3), pages 458-467, April.
    3. von der Gracht, Heiko A., 2012. "Consensus measurement in Delphi studies," Technological Forecasting and Social Change, Elsevier, vol. 79(8), pages 1525-1536.
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    2. 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.
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    4. Huang, Ying & Porter, Alan L. & Zhang, Yi & Lian, Xiangpeng & Guo, Ying, 2019. "An assessment of technology forecasting: Revisiting earlier analyses on dye-sensitized solar cells (DSSCs)," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 831-843.

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