Testing best practices to reduce the overconfidence bias in multi-criteria decision analysis

Valentina Ferretti; Sule Guney; Gilberto Montibeller; Detlof Von Winterfeldt

doi:10.1109/HICSS.2016.195

Testing best practices to reduce the overconfidence bias in multi-criteria decision analysis

Valentina Ferretti
, Sule Guney
, Gilberto Montibeller
, Detlof Von Winterfeldt

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

15 Scopus citations

Abstract

This paper explores the effectiveness of several methods to reduce the overconfidence bias when eliciting continuous probability distributions in the context of multicriteria decision analysis. We examine the effectiveness of using a fixed value method (as opposed to the standard fixed probability method) and the use of counterfactuals and hypothetical bets to increase the range of the distributions and to correct possible median displacements. The results show that the betting procedure to correct the median is quite effective, but the methods to increase the range of estimates have only a have small, but positive effect.

Original language	English
Title of host publication	Proceedings of the 49th Annual Hawaii International Conference on System Sciences, HICSS 2016
Editors	Ralph H. Sprague, Tung X. Bui
Publisher	IEEE Computer Society
Pages	1547-1555
Number of pages	9
ISBN (Electronic)	9780769556703
DOIs	https://doi.org/10.1109/HICSS.2016.195
State	Published - 7 Mar 2016
Externally published	Yes
Event	49th Annual Hawaii International Conference on System Sciences, HICSS 2016 - Koloa, United States Duration: 5 Jan 2016 → 8 Jan 2016

Publication series

Name	Proceedings of the Annual Hawaii International Conference on System Sciences
Volume	2016-March
ISSN (Print)	1530-1605

Conference

Conference	49th Annual Hawaii International Conference on System Sciences, HICSS 2016
Country/Territory	United States
City	Koloa
Period	5/01/16 → 8/01/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

ASJC Scopus subject areas

General Engineering

Access to Document

10.1109/HICSS.2016.195

Cite this

Ferretti, V., Guney, S., Montibeller, G., & Winterfeldt, D. V. (2016). Testing best practices to reduce the overconfidence bias in multi-criteria decision analysis. In R. H. Sprague, & T. X. Bui (Eds.), Proceedings of the 49th Annual Hawaii International Conference on System Sciences, HICSS 2016 (pp. 1547-1555). Article 7427374 (Proceedings of the Annual Hawaii International Conference on System Sciences; Vol. 2016-March). IEEE Computer Society. https://doi.org/10.1109/HICSS.2016.195

Ferretti, Valentina ; Guney, Sule ; Montibeller, Gilberto et al. / Testing best practices to reduce the overconfidence bias in multi-criteria decision analysis. Proceedings of the 49th Annual Hawaii International Conference on System Sciences, HICSS 2016. editor / Ralph H. Sprague ; Tung X. Bui. IEEE Computer Society, 2016. pp. 1547-1555 (Proceedings of the Annual Hawaii International Conference on System Sciences).

@inproceedings{c781ba0de9e24b92bee93e3bb417ad55,

title = "Testing best practices to reduce the overconfidence bias in multi-criteria decision analysis",

abstract = "This paper explores the effectiveness of several methods to reduce the overconfidence bias when eliciting continuous probability distributions in the context of multicriteria decision analysis. We examine the effectiveness of using a fixed value method (as opposed to the standard fixed probability method) and the use of counterfactuals and hypothetical bets to increase the range of the distributions and to correct possible median displacements. The results show that the betting procedure to correct the median is quite effective, but the methods to increase the range of estimates have only a have small, but positive effect.",

author = "Valentina Ferretti and Sule Guney and Gilberto Montibeller and Winterfeldt, \{Detlof Von\}",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 49th Annual Hawaii International Conference on System Sciences, HICSS 2016 ; Conference date: 05-01-2016 Through 08-01-2016",

year = "2016",

month = mar,

day = "7",

doi = "10.1109/HICSS.2016.195",

language = "English",

series = "Proceedings of the Annual Hawaii International Conference on System Sciences",

publisher = "IEEE Computer Society",

pages = "1547--1555",

editor = "Sprague, \{Ralph H.\} and Bui, \{Tung X.\}",

booktitle = "Proceedings of the 49th Annual Hawaii International Conference on System Sciences, HICSS 2016",

address = "United States",

}

Ferretti, V, Guney, S, Montibeller, G & Winterfeldt, DV 2016, Testing best practices to reduce the overconfidence bias in multi-criteria decision analysis. in RH Sprague & TX Bui (eds), Proceedings of the 49th Annual Hawaii International Conference on System Sciences, HICSS 2016., 7427374, Proceedings of the Annual Hawaii International Conference on System Sciences, vol. 2016-March, IEEE Computer Society, pp. 1547-1555, 49th Annual Hawaii International Conference on System Sciences, HICSS 2016, Koloa, United States, 5/01/16. https://doi.org/10.1109/HICSS.2016.195

Testing best practices to reduce the overconfidence bias in multi-criteria decision analysis. / Ferretti, Valentina; Guney, Sule; Montibeller, Gilberto et al.
Proceedings of the 49th Annual Hawaii International Conference on System Sciences, HICSS 2016. ed. / Ralph H. Sprague; Tung X. Bui. IEEE Computer Society, 2016. p. 1547-1555 7427374 (Proceedings of the Annual Hawaii International Conference on System Sciences; Vol. 2016-March).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Testing best practices to reduce the overconfidence bias in multi-criteria decision analysis

AU - Ferretti, Valentina

AU - Guney, Sule

AU - Montibeller, Gilberto

AU - Winterfeldt, Detlof Von

PY - 2016/3/7

Y1 - 2016/3/7

N2 - This paper explores the effectiveness of several methods to reduce the overconfidence bias when eliciting continuous probability distributions in the context of multicriteria decision analysis. We examine the effectiveness of using a fixed value method (as opposed to the standard fixed probability method) and the use of counterfactuals and hypothetical bets to increase the range of the distributions and to correct possible median displacements. The results show that the betting procedure to correct the median is quite effective, but the methods to increase the range of estimates have only a have small, but positive effect.

AB - This paper explores the effectiveness of several methods to reduce the overconfidence bias when eliciting continuous probability distributions in the context of multicriteria decision analysis. We examine the effectiveness of using a fixed value method (as opposed to the standard fixed probability method) and the use of counterfactuals and hypothetical bets to increase the range of the distributions and to correct possible median displacements. The results show that the betting procedure to correct the median is quite effective, but the methods to increase the range of estimates have only a have small, but positive effect.

UR - https://www.scopus.com/pages/publications/84975480900

U2 - 10.1109/HICSS.2016.195

DO - 10.1109/HICSS.2016.195

M3 - Conference contribution

AN - SCOPUS:84975480900

T3 - Proceedings of the Annual Hawaii International Conference on System Sciences

SP - 1547

EP - 1555

BT - Proceedings of the 49th Annual Hawaii International Conference on System Sciences, HICSS 2016

A2 - Sprague, Ralph H.

A2 - Bui, Tung X.

PB - IEEE Computer Society

T2 - 49th Annual Hawaii International Conference on System Sciences, HICSS 2016

Y2 - 5 January 2016 through 8 January 2016

ER -

Ferretti V, Guney S, Montibeller G, Winterfeldt DV. Testing best practices to reduce the overconfidence bias in multi-criteria decision analysis. In Sprague RH, Bui TX, editors, Proceedings of the 49th Annual Hawaii International Conference on System Sciences, HICSS 2016. IEEE Computer Society. 2016. p. 1547-1555. 7427374. (Proceedings of the Annual Hawaii International Conference on System Sciences). doi: 10.1109/HICSS.2016.195

Testing best practices to reduce the overconfidence bias in multi-criteria decision analysis

Abstract

Publication series

Conference

Bibliographical note

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this