The influence of cognitive bias on crisis decision-making: Experimental evidence on the comparison of bias effects between crisis decision-maker groups

Journal Article (2022)
Author(s)

David Paulus (TU Delft - Organisation & Governance)

Gerdien de Vries (TU Delft - Organisation & Governance)

M.F.W.H.A. Janssen (TU Delft - Engineering, Systems and Services)

Bartel Van de Walle (UNU-MERIT)

Research Group
Organisation & Governance
Copyright
© 2022 D. Paulus, G. de Vries, M.F.W.H.A. Janssen, Bartel Van de Walle
DOI related publication
https://doi.org/10.1016/j.ijdrr.2022.103379
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 D. Paulus, G. de Vries, M.F.W.H.A. Janssen, Bartel Van de Walle
Research Group
Organisation & Governance
Volume number
82
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Abstract

A crisis requires the affected population, governments or non-profit organizations, as well as crisis experts, to make urgent and sometimes life-critical decisions. With the urgency and uncertainty they create, crises are particularly amenable to inducing cognitive biases that influence decisionmaking. However, there is limited empirical evidence regarding the impact of cognitive biases on estimation, judgment, and decision-making tasks in crises. Possible biases occurring in crises are: (1) to be influenced by how information is framed (i.e., framing effect), (2) to overly rely on information that confirms rather than opposes preliminary assumptions (i.e., confirmation bias), (3) to rely heavily on a skewed informational cue when making estimations (i.e., anchoring bias), and (4) to see the own decision-making as less biased than decision-making of others (i.e., bias blind spot). We investigate these four cognitive biases using three online survey experiments targeting crisis-affected people of the general public (n = 460, mTurk workers), governmental and non-profit workers (n = 50, mTurk workers), and crisis experts (n = 21, purposefully
sampled). Our findings show that crisis experts are the least biased group but are still significantly affected by anchoring, framing, and bias blind spot. Crisis-affected people from the general public showed the strongest susceptibility to all four biases studied. The findings have implications for future research on crisis information systems (IS) design. As crisis response is increasingly facilitated through IS, we propose debiasing functions that account for biased user behavior in crises.