
Thumbs Up or Down: Consumer Reactions to Decisions by Algorithms Versus Humans
Author(s) -
Gizem Yalcin,
Sarah Lim,
Stefano Puntoni,
Stijn M. J. van Osselaer
Publication year - 2022
Publication title -
journal of marketing research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.321
H-Index - 171
eISSN - 1547-7193
pISSN - 0022-2437
DOI - 10.1177/00222437211070016
Subject(s) - outcome (game theory) , decision maker , attribution , computer science , decision analysis , psychology , marketing , algorithm , economics , management science , social psychology , business , microeconomics , mathematical economics
Although companies increasingly are adopting algorithms for consumer-facing tasks (e.g., application evaluations), little research has compared consumers’ reactions to favorable decisions (e.g., acceptances) versus unfavorable decisions (e.g., rejections) about themselves that are made by an algorithm versus a human. Ten studies reveal that, in contrast to managers’ predictions, consumers react less positively when a favorable decision is made by an algorithmic (vs. a human) decision maker, whereas this difference is mitigated for an unfavorable decision. The effect is driven by distinct attribution processes: it is easier for consumers to internalize a favorable decision outcome that is rendered by a human than by an algorithm, but it is easy to externalize an unfavorable decision outcome regardless of the decision maker type. The authors conclude by advising managers on how to limit the likelihood of less positive reactions toward algorithmic (vs. human) acceptances.