Delphi method

The Delphi method or Delphi technique (/ˈdɛlf/ DEL-fy; also known as Estimate-Talk-Estimate or ETE) is a structured communication technique or method, originally developed as a systematic, interactive forecasting method that relies on a panel of experts.[1][2][3][4][5] Delphi has been widely used for business forecasting and has certain advantages over another structured forecasting approach, prediction markets.[6]

Delphi can also be used to help reach expert consensus and develop professional guidelines.[7] It is used for such purposes in many health-related fields, including clinical medicine, public health, and research.[7][8]

Delphi is based on the principle that forecasts (or decisions) from a structured group of individuals are more accurate than those from unstructured groups.[9] The experts answer questionnaires in two or more rounds. After each round, a facilitator or change agent[10] provides an anonymised summary of the experts' forecasts from the previous round as well as the reasons they provided for their judgments. Thus, experts are encouraged to revise their earlier answers in light of the replies of other members of their panel. It is believed that during this process the range of the answers will decrease and the group will converge towards the "correct" answer. Finally, the process is stopped after a predefined stopping criterion (e.g., number of rounds, achievement of consensus, stability of results), and the mean or median scores of the final rounds determine the results.[11]

Special attention has to be paid to the formulation of the Delphi theses and the definition and selection of the experts in order to avoid methodological weaknesses that severely threaten the validity and reliability of the results.[12][13]

  1. ^ Dalkey N, Helmer O (1963). "An Experimental Application of the Delphi Method to the use of experts". Management Science. 9 (3): 458–467. doi:10.1287/mnsc.9.3.458. hdl:2027/inu.30000029301680.
  2. ^ Brown BB (September 1968). Delphi Process: A Methodology Used for the Elicitation of Opinions of Experts (Report). Santa Monica CA: Rand Corp. P-3925.
  3. ^ Sackman H (1974). Delphi assessment: Expert opinion, forecasting, and group process (Report). Santa Monica CA: The Rand Corporation. R-1283-PR.
  4. ^ Brown T (1972). An Experiment in Probabilistic Forecasting (Report). Santa Monica CA: The Rand Corporation. R-944-ARPA.
  5. ^ Linstone HA, Turoff M, eds. (1975). The Delphi Method: Techniques and Applications. Reading, Mass.: Addison-Wesley. ISBN 978-0-201-04294-8. Archived from the original on 2008-05-20.
  6. ^ Cite error: The named reference Green_2008 was invoked but never defined (see the help page).
  7. ^ a b Cite error: The named reference Taylor2020 was invoked but never defined (see the help page).
  8. ^ Cite error: The named reference Moher2010 was invoked but never defined (see the help page).
  9. ^ Rowe G, Wright G (2001). "Expert Opinions in Forecasting: The Role of the Delphi Technique" (PDF). In Armstrong (ed.). Principles of Forecasting: A Handbook of Researchers and Practitioners. International Series in Operations Research & Management Science. Vol. 30. Boston: Kluwer Academic Publishers. pp. 125–144. doi:10.1007/978-0-306-47630-3_7. ISBN 978-0-7923-7401-5.
  10. ^ McLaughlin MW (1990). "The Rand Change Agent Study Revisited: Macro Perspectives and Micro Realities". Educational Researcher. 19 (9): 11–16. ISSN 0013-189X. JSTOR 1176973.
  11. ^ Rowe G, Wright G (October 1999). "The Delphi technique as a forecasting tool: issues and analysis". International Journal of Forecasting. 15 (4): 353–375. doi:10.1016/S0169-2070(99)00018-7. S2CID 10745965.
  12. ^ Markmann C, Spickermann A, von der Gracht HA, Brem A (March 2021). "Improving the question formulation in Delphi-like surveys: Analysis of the effects of abstract language and amount of information on response behavior". Futures & Foresight Science. 3 (1): e56. doi:10.1002/ffo2.56. S2CID 225273393.
  13. ^ Mauksch S, Heiko A, Gordon TJ (May 2020). "Who is an expert for foresight? A review of identification methods". Technological Forecasting and Social Change. 154: 119982. doi:10.1016/j.techfore.2020.119982. S2CID 216161197.

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