EURO 2025 Leeds
Abstract Submission

1627. Anchoring bias in the tradeoff procedure within Multi-Attribute Value Theory

Invited abstract in session MC-61: Advances in behavioral decision analysis 2, stream Behavioural OR.

Monday, 12:30-14:00
Room: Maurice Keyworth G.31

Authors (first author is the speaker)

1. Geqie Sun
TPM, Delft University of Technology
2. Maarten Kroesen
3. Jafar Rezaei
Engineering Systems and Services, Delft University of Technology

Abstract

Eliciting the weights of attributes is one of the key steps in multi-attribute decision-making methods. The weights represent the relative importance, contribution, or influence of the attributes in forming a decision. There exist various weight elicitation methods, each with different assumptions and procedures, though most fail to account for the effect of cognitive bias in their procedures. This study examines anchoring bias, a well-known cognitive bias, in the weight elicitation step (the Tradeoff procedure) of multi-attribute value theory (MAVT). We developed three hypotheses: (i) Using the most important (best) attribute to construct the indifference pairs in the Tradeoff procedure leads to higher weights for the best and worst attributes and lower weights for the other attributes, (ii) Using the least important (worst) attribute to construct the indifference pairs in the Tradeoff procedure leads to lower weights for the best and worst attributes and higher weights for the other attributes, (iii) Using both best and worst attributes to construct the indifference pairs (i.e., the Best-Worst Tradeoff (BWT) method), mitigates anchoring bias. To test the hypotheses, we conducted an experiment by designing a questionnaire based on the MAVT methodology and collected data from 336 participants for a decision problem. The findings indicate that anchoring bias has a significant impact on the Tradeoff procedure, and that the BWT is effective in reducing this bias.

Keywords

Status: accepted

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