Expert Opinions in Forecasting: The Role of the Delphi Technique

By G. Rowe, George Wright. 2001

853 citations recorded by the source corpus.

Subfields: General Decision Sciences, Management Science and Operations Research, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/e315327ee3c6eebbb18152b9d9d97c1e31006b58

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Citations in the corpus

Forecasting: theory and practice (2020, background): “It is a multipleround survey in which experts participate anonymously to provide their forecasts and feedback (Rowe and Wright, 2001).”
What is societal impact of research and how can it be assessed? a literature survey (2013, neutral): “A first report of the project (Centre for Quality and Change Management, 2011) presented the results of a Delphi study (Rowe & Wright, 2001).”
Managing Functional Biases in Organizational Forecasts: A Case Study of Consensus Forecasting in Supply Chain Planning (2009, methodology): “The most popular structured, non-interacting, group forecasting approach is the Delphi method wherein a group’s successive individual forecasts elicits anonymous feedback in the form of summary statistics (Rowe and Wright, 2001).”
Validating an innovative real-time Delphi approach - A methodological comparison between real-time and conventional Delphi studies (2011, methodology): “Since the design of the survey questionnaire is of utmost importance for a study's success, the same comprehensive procedure and rules to develop adequate projections were followed for both studies [32–34].”
Bayesian forecasting of immigration to selected European countries by using expert knowledge (2010, background): “Rowe and Wright (2001) have provided evidence for a strong influence of question formulation on the answers that are obtained.”
Forecasting and operational research: a review (2008, methodology): “Methods include Delphi, a modified and anonimised committee forecast (Rowe and Wright, 2001), and intentions-to-buy surveys, which, with modifications, can prove predictive of future sales (Morwitz, 2001; Murthy, 2007).”
Findings from Evidence-Based Forecasting: Methods for Reducing Forecast Error (2006, neutral): “However, there have been only a few multiple hypotheses tests on Delphi, with most of these of recent origin; Rowe and Wright (2001) found ten tests in the past 25 years.”
Heading towards a multimodal city of the future (2014, background): “104]: among others concerning nonambiguity, exclusion of conditional statements, explanation of scientific or technological terms [103,105], balance of conciseness and length [106,107], and optimal processing time reflected in length of the survey [97,108].”
Golden Rule of Forecasting: Be conservative (2015, neutral): “A review of the literature concluded that Delphi provided forecasts that were more accurate than forecasts from traditional face-toface meetings in five studies and less accurate in one; two studies showed no difference (Rowe and Wright, 2001).”
Desirability bias in foresight: Consequences for decision quality based on Delphi results (2011, methodology): “In addition, we followed established quality guidelines for the formulation of our projections that the projections should not be ambiguous, include conditional statements, use unknown scientific or technological terms, but should use common definitions [61–63].”
Structured elicitation of expert judgments for threatened species assessment: a case study on a continental scale using email (2012, neutral): “In the classical Delphi process (Dalkey & Helmer 1963; Linstone & Turoff 1975; Rowe & Wright 2001), experts make an initial estimate, are provided with anonymous feedback about the estimates of the other group members and then make a second, revised estimate, with the estimate and feedback rounds…”
Using Delphi technique to build consensus in practice (2014, methodology): “Thus, Delphi is used in forecasting tasks when there is no appropriate or available information and is based on the assumption that “N+1 heads are better than one” (Hill, 1982; Nerantzidis, 2012; Rowe & Wright, 2001).”
A review of studies on expert estimation of software development effort (2004, methodology): “One may take the average of individual software development effort estimates (H€ost and Wohlin, 1998), apply a structured software estimation group process (Taff et al., 1991), select the expert with the best estimate on the previous task (Ringuest and Tang, 1987), or apply the well-documented Delph”
Consensus measurement in Delphi studies (2012, background): “Rowe andWright [10] added that the use of a trimmed mean that excludes these extreme values could also be a solution to the problem.”
Forecasting for Marketing (2005, neutral): “For a summary of the evidence on the accuracy of Delphi versus unstructured judgment, see Rowe and Wright (2001).”