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A Fuzzy Delphi Consensus Methodology Based on a Fuzzy Ranking

Author

Listed:
  • Antonio Francisco Roldán López de Hierro

    (Department of Statistics and Operations Research, University of Granada, 18010 Granada, Spain)

  • Miguel Sánchez

    (Juan XXIII Secondary School, 18010 Granada, Spain)

  • Daniel Puente-Fernández

    (Department of Nursing, Mind, Brain and Behavior Research Center (CIMCYC-UGR), University of Granada, 18010 Granada, Spain)

  • Rafael Montoya-Juárez

    (Department of Nursing, Mind, Brain and Behavior Research Center (CIMCYC-UGR), University of Granada, 18010 Granada, Spain)

  • Concepción Roldán

    (Department of Statistics and Operations Research, University of Granada, 18010 Granada, Spain)

Abstract

Delphi multi-round survey is a procedure that has been widely and successfully used to aggregate experts’ opinions about some previously established statements or questions. Such opinions are usually expressed as real numbers and some commentaries. The evolution of the consensus can be shown by an increase in the agreement percentages, and a decrease in the number of comments made. A consensus is reached when this percentage exceeds a certain previously set threshold. If this threshold has not been reached, the moderator modifies the questionnaire according to the comments he/she has collected, and the following round begins. In this paper, a new fuzzy Delphi method is introduced. On the one hand, the experts’ subjective judgments are collected as fuzzy numbers, enriching the approach. On the other hand, such opinions are collected through a computerized application that is able to interpret the experts’ opinions as fuzzy numbers. Finally, we employ a recently introduced fuzzy ranking methodology, satisfying many properties according to human intuition, in order to determine whether the expert’s fuzzy opinion is favorable enough (comparing with a fixed fuzzy number that indicates Agree or Strongly Agree). A cross-cultural validation was performed to illustrate the applicability of the proposed method. The proposed approach is simple for two reasons: it does not need a defuzzification step of the experts’ answers, and it can consider a wide range of fuzzy numbers not only triangular or trapezoidal fuzzy numbers.

Suggested Citation

  • Antonio Francisco Roldán López de Hierro & Miguel Sánchez & Daniel Puente-Fernández & Rafael Montoya-Juárez & Concepción Roldán, 2021. "A Fuzzy Delphi Consensus Methodology Based on a Fuzzy Ranking," Mathematics, MDPI, vol. 9(18), pages 1-18, September.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:18:p:2323-:d:639028
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    References listed on IDEAS

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    1. Azemeraw Tadesse Mengistu & Roberto Panizzolo, 2021. "Indicators and Framework for Measuring Industrial Sustainability in Italian Footwear Small and Medium Enterprises," Sustainability, MDPI, vol. 13(10), pages 1-20, May.
    2. Hao-Chang Tsai & An-Sheng Lee & Huang-Ning Lee & Chien-Nan Chen & Yu-Chun Liu, 2020. "An Application of the Fuzzy Delphi Method and Fuzzy AHP on the Discussion of Training Indicators for the Regional Competition, Taiwan National Skills Competition, in the Trade of Joinery," Sustainability, MDPI, vol. 12(10), pages 1-19, May.
    3. 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.
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