Anchoring Bias in Value Function Elicitation Within Multiattribute Value Theory

Journal Article (2025)
Author(s)

G. Sun (TU Delft - Transport and Logistics)

M. Kroesen (TU Delft - Transport and Logistics)

J. Rezaei (TU Delft - Transport and Logistics)

Research Group
Transport and Logistics
DOI related publication
https://doi.org/10.1287/deca.2024.0308
More Info
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Publication Year
2025
Language
English
Research Group
Transport and Logistics
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository as part of the Taverne amendment. More information about this copyright law amendment can be found at https://www.openaccess.nl. Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Issue number
4
Volume number
22
Pages (from-to)
284-304
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Abstract

Anchoring bias refers to the human tendency to rely heavily on an initial piece of information when making judgments. This bias has significant implications for decision analysis methods that rely on human judgments. This study examines the influence of anchoring bias in the value function elicitation step of the multiattribute value theory, specifically within the midvalue splitting procedure. We hypothesize that the starting point provided by the analyst during elicitation creates a bias in decision makers’ judgments, leading to distorted value functions and ultimately affecting decision outcomes. We also hypothesize that counter-anchoring and avoiding the use of anchors mitigate the effect of anchoring bias. To test the hypotheses, we designed an experiment and collected data from 320 subjects. The findings show that the starting point in the midvalue splitting procedure could change the attribute-specific value functions and, consequently, the overall value of the alternatives. Additionally, two debiasing strategies, counter-anchoring and avoiding the use of anchors, were found to be effective in reducing the effect of anchoring bias. The implications of this study can extend to other structured value function elicitation methods.

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