دانلود مقاله ISI انگلیسی شماره 76749
ترجمه فارسی عنوان مقاله

تاثیر مطلوبیت در آینده نگری: پیامدها برای کیفیت تصمیم گیری بر اساس نتایج دلفی

عنوان انگلیسی
Desirability bias in foresight: Consequences for decision quality based on Delphi results
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
76749 2011 17 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Technological Forecasting and Social Change, Volume 78, Issue 9, November 2011, Pages 1654–1670

ترجمه کلمات کلیدی
تاثیر مطلوبیت؛ دلفی؛ آینده نگری؛ کیفیت تصمیم گیری بر اساس دلفی
کلمات کلیدی انگلیسی
Desirability bias; Delphi; Foresight; Delphi based decision quality
پیش نمایش مقاله
پیش نمایش مقاله  تاثیر مطلوبیت در آینده نگری: پیامدها برای کیفیت تصمیم گیری بر اساس نتایج دلفی

چکیده انگلیسی

In foresight activities uncertainty is high and decision makers frequently have to rely on human judgment. Human judgment, however, is subject to numerous cognitive biases. In this paper, we study the effects of the desirability bias in foresight. We analyze data from six Delphi studies and observe that participants systematically estimate the probability of occurrence for desirable (undesirable) future projections higher (lower) than the probability for projections with neutral desirability. We also demonstrate that in the course of a multi-round Delphi process, this bias decreases but is not necessarily eliminated. Arguably, the quality of decisions based on Delphi results may be adversely affected if experts share a pronounced and common desirability for a future projection. Researchers and decision makers have to be aware of the existence and potential consequences of such a desirability bias in Delphi studies when interpreting their results and taking decisions. We propose a post-hoc procedure to identify and quantify the extent to which the desirability bias affects Delphi results. The results of this post-hoc procedure complement traditional Delphi results; they provide researchers and decision makers with information on when and to which extent results of Delphi-based foresight may be biased.