Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/281562 
Year of Publication: 
2021
Citation: 
[Journal:] Amfiteatru Economic Journal [ISSN:] 2247-9104 [Volume:] 23 [Issue:] 56 [Year:] 2021 [Pages:] 102-119
Publisher: 
The Bucharest University of Economic Studies, Bucharest
Abstract: 
Companies are increasingly adopting Artificial Intelligence (AI) today. Recently however debates started over the risk of human cognitive biases being replicated (and scaled) by AI. Research on biases in AI predicting consumer choice is incipient and focuses on observable biases. We provide a short synthesis of cognitive biases and their potential risk of being replicated in AI-based choice prediction. We also discuss for the first time the risk of unobservable biases, which affect choice indirectly, through other biases. We exemplify this by looking at looking at three prevalent, most frequently investigated biases in consumer behaviour: extremeness aversion, regret aversion and cognitive regulatory focus (prevention- versus promotion-focus). Based on a sample of 1747 respondents, through partial least squares structural equation modelling and significance testing, we show that regret aversion (unobservable bias) significantly reduces extremeness aversion (observable bias) and mediates the influence of cognitive regulatory focus (unobservable bias).
Subjects: 
cognitive bias
artificial intelligence
choice prediction
consumer choice behaviour
regret aversion
extremeness aversion
regulatory focus
JEL: 
D91
D80
D01
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.