Use of expert knowledge to anticipate the future: issues, analysis and directions

Fergus Bolger, George Wright

    Research output: Contribution to journalArticle

    9 Citations (Scopus)

    Abstract

    Unless the anticipation problem is routine and short-term, and objective data are plentiful, expert judgment will be needed. Risk assessment is analogous to anticipation of the future in that models need to be developed and applied to data. Since objective data are often scanty, expert knowledge elicitation (EKE) techniques have been developed for risk assessment that allow model development and parametrization using expert judgments with minimal cognitive and social biases. Here, we conceptualize how EKE can be developed and applied to support anticipation of the future. Accordingly, we first define EKE as an entire process, that involves considering experts as a source of data, and that comprises various methods for ensuring the quality of this data, including – selecting the best experts, training experts in normative aspects of anticipation, and combining judgments of several experts – as well as eliciting unbiased estimates and constructs from experts. We detail aspects of the papers that constitute the Special Issue and analyse these in terms of the stages within the EKE future-anticipation process that they address. We identify the remaining gaps in our knowledge. Our conceptualization of EKE to support anticipation of the future is compared and contrasted with the extant research effort into judgmental forecasting.
    LanguageEnglish
    Pages230-243
    Number of pages13
    JournalInternational Journal of Forecasting
    Volume33
    Issue number1
    Early online date10 Dec 2016
    DOIs
    Publication statusPublished - 1 Jan 2017

    Fingerprint

    Knowledge acquisition
    Knowledge Elicitation
    Anticipation
    Risk assessment
    Expert Judgment
    Risk Assessment
    Knowledge
    Expert knowledge
    Knowledge elicitation
    Parametrization
    Forecasting
    Entire

    Keywords

    • expert knowledge elicitation
    • risk assessment
    • forecasting
    • scenario planning

    Cite this

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    abstract = "Unless the anticipation problem is routine and short-term, and objective data are plentiful, expert judgment will be needed. Risk assessment is analogous to anticipation of the future in that models need to be developed and applied to data. Since objective data are often scanty, expert knowledge elicitation (EKE) techniques have been developed for risk assessment that allow model development and parametrization using expert judgments with minimal cognitive and social biases. Here, we conceptualize how EKE can be developed and applied to support anticipation of the future. Accordingly, we first define EKE as an entire process, that involves considering experts as a source of data, and that comprises various methods for ensuring the quality of this data, including – selecting the best experts, training experts in normative aspects of anticipation, and combining judgments of several experts – as well as eliciting unbiased estimates and constructs from experts. We detail aspects of the papers that constitute the Special Issue and analyse these in terms of the stages within the EKE future-anticipation process that they address. We identify the remaining gaps in our knowledge. Our conceptualization of EKE to support anticipation of the future is compared and contrasted with the extant research effort into judgmental forecasting.",
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    Use of expert knowledge to anticipate the future : issues, analysis and directions. / Bolger, Fergus; Wright, George.

    In: International Journal of Forecasting, Vol. 33, No. 1, 01.01.2017, p. 230-243.

    Research output: Contribution to journalArticle

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