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Anchoring Bias in Value Function Elicitation Within Multiattribute Value Theory

Geqie Sun,Maarten Kroesen,Jafar Rezaei

Published 2025 in Decision Analytics

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. Supplemental Material: The online appendix is available at https://doi.org/10.1287/deca.2024.0308 .

PUBLICATION RECORD

  • Publication year

    2025

  • Venue

    Decision Analytics

  • Publication date

    2025-07-31

  • Fields of study

    Computer Science, Business, Economics, Psychology

  • Identifiers
    DOI 10.1287/deca.2024.0308
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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