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Structured analogies for forecasting

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Author Info
Kesten C. Green
J. Scott Armstrong

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Abstract

When people forecast, they often use analogies but in an unstructured manner. We propose a structured judgmental procedure that involves asking experts to list as many analogies as they can, rate how similar the analogies are to the target situation, and match the outcomes of the analogies with possible outcomes of the target. An administrator would then derive a forecast from the experts' information. We compared structured analogies with unaided judgments for predicting the decisions made in eight conflict situations. These were difficult forecasting problems; the 32% accuracy of the unaided experts was only slightly better than chance. In contrast, 46% of structured analogies forecasts were accurate. Among experts who were independently able to think of two or more analogies and who had direct experience with their closest analogy, 60% of forecasts were accurate. Collaboration did not improve accuracy.

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File URL: http://www.buseco.monash.edu.au/depts/ebs/pubs/wpapers/2004/wp17-04.pdf
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Publisher Info
Paper provided by Monash University, Department of Econometrics and Business Statistics in its series Monash Econometrics and Business Statistics Working Papers with number 17/04.

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Length: 27 pages
Date of creation: Nov 2004
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Handle: RePEc:msh:ebswps:2004-17

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Related research
Keywords: accuracy; analogies; collaboration; conflict; expert; forecasting; judgment.;

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Find related papers by JEL classification:
D74 - Microeconomics - - Analysis of Collective Decision-Making - - - Conflict; Conflict Resolution; Alliances

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Green, Kesten C., 2002. "Forecasting decisions in conflict situations: a comparison of game theory, role-playing, and unaided judgement," International Journal of Forecasting, Elsevier, vol. 18(3), pages 321-344. [Downloadable!] (restricted)
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. J. Scott Armstrong & Kesten C. Green, 2005. "Demand Forecasting: Evidence-based Methods," Monash Econometrics and Business Statistics Working Papers 24/05, Monash University, Department of Econometrics and Business Statistics. [Downloadable!]
  2. Althuizen, N.A.P. & Wierenga, B., 2008. "The Value of Analogical Reasoning for the Design of Creative Sales Promotion Campaigns: A Case-Based Reasoning Approach," Research Paper ERS-2008-006-MKT Revision, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni. [Downloadable!]
  3. Green, Kesten C., 2008. "Assessing probabilistic forecasts about particular situations," MPRA Paper 8836, University Library of Munich, Germany. [Downloadable!]
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