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Over-optimism Among Experts in Assessment and Foresight

  • Gunther Tichy
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    It is still disputed whether foresight exercises should be based on top-expert assessments or on a broader base of less specialised experts, and whether the self-rating of experts is an acceptable method. Using the German 1993 and the Austrian 1998 Technology Delphis, this study addresses both questions: Self-rating is in fact an appropriate method for selecting experts. But the assessment of self-rated top-experts tend to suffer from an optimism bias, due to the experts’ involvement and their underestimation of realisation and diffusion problems. The degree of optimism is positively correlated with the degree of self-rated knowledge, and it is more pronounced for the least pioneering and for organisational innovations. Experts with top self-ratings working in business have a stronger optimism bias than those working in academia or in the administration. Consistent with the insider hypothesis, they are most optimistic with regard to realisation, innovativeness, and potential leadership in economic exploitation. Given the optimism bias, foresight exercises should base their panels on a fair mixture of experts of different grades, with different types of knowledge and affiliation, and not only on top specialists of the respective field. Delphi-type exercises, therefore, offer an advantage relative to forum groups or small panels of specialists.

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    Paper provided by Institute of Technology Assessment (ITA) in its series ITA manu:scripts with number 02_05.

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    Date of creation: 10 Oct 2002
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    Handle: RePEc:ita:itaman:02_05
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    1. Georg Aichholzer, 2001. "Delphi Austria - An Example of Tailoring Foresight to the Needs of a Small Country," ITA manu:scripts 01_02, Institute of Technology Assessment (ITA).
    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. C. West Churchman, 1963. "The X of X," Management Science, INFORMS, vol. 9(3), pages 351-357, April.
    4. JS Armstrong, 2004. "Forecasting Methods for Conflict Situations," General Economics and Teaching 0412025, EconWPA.
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