When Algorithms Fail Consumers' Responses to Brand Harm Crises Caused by Algorithm Errors

Algorithms, increasingly used by brands, sometimes fail to perform as expected or, even worse, cause harm, leading to brand harm crises. Algorithm failures are unfortunately increasing in frequency, yet little is known about consumers' responses to brands following such crises. Extending develo...

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Published inJournal of marketing Vol. 85; no. 5; pp. 74 - 94
Main Authors Srinivasan, Raji, Sarial-Abi, Gülen
Format Journal Article
LanguageEnglish
Published Los Angeles, CA Sage Publications, Inc 01.09.2021
SAGE Publications
SAGE PUBLICATIONS, INC
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Online AccessGet full text
ISSN0022-2429
1547-7185
DOI10.1177/0022242921997082

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Abstract Algorithms, increasingly used by brands, sometimes fail to perform as expected or, even worse, cause harm, leading to brand harm crises. Algorithm failures are unfortunately increasing in frequency, yet little is known about consumers' responses to brands following such crises. Extending developments in the theory of mind perception, the authors hypothesize that, following a brand harm crisis, consumers respond less negatively if the error was caused by an algorithm (vs. a human). The authors further hypothesize that consumers' lower mind perception of agency of the algorithm (vs. a human), which lowers their perceptions of the algorithm's responsibility for the harm, mediates this relationship. Four moderators of this relationship are hypothesized: two algorithm characteristics (whether the algorithm is anthropomorphized and whether it involves machine learning) and two characteristics of the task for which the algorithm is deployed (whether the task is subjective [vs. objective] and whether it is interactive [vs. noninteractive]). The authors find support for the hypotheses in eight experimental studies. The effects of two managerial interventions to manage brand harmcrises caused by algorithm errors are examined. This research advances the literature on brand harm crises, algorithm usage, and algorithmic marketing and generates managerial guidelines to address such crises.
AbstractList Algorithms, increasingly used by brands, sometimes fail to perform as expected or, even worse, cause harm, leading to brand harm crises. Algorithm failures are unfortunately increasing in frequency, yet little is known about consumers’ responses to brands following such crises. Extending developments in the theory of mind perception, the authors hypothesize that, following a brand harm crisis, consumers respond less negatively if the error was caused by an algorithm (vs. a human). The authors further hypothesize that consumers’ lower mind perception of agency of the algorithm (vs. a human), which lowers their perceptions of the algorithm’s responsibility for the harm, mediates this relationship. Four moderators of this relationship are hypothesized: two algorithm characteristics (whether the algorithm is anthropomorphized and whether it involves machine learning) and two characteristics of the task for which the algorithm is deployed (whether the task is subjective [vs. objective] and whether it is interactive [vs. noninteractive]). The authors find support for the hypotheses in eight experimental studies. The effects of two managerial interventions to manage brand harm crises caused by algorithm errors are examined. This research advances the literature on brand harm crises, algorithm usage, and algorithmic marketing and generates managerial guidelines to address such crises.
Algorithms, increasingly used by brands, sometimes fail to perform as expected or, even worse, cause harm, leading to brand harm crises. Algorithm failures are unfortunately increasing in frequency, yet little is known about consumers' responses to brands following such crises. Extending developments in the theory of mind perception, the authors hypothesize that, following a brand harm crisis, consumers respond less negatively if the error was caused by an algorithm (vs. a human). The authors further hypothesize that consumers' lower mind perception of agency of the algorithm (vs. a human), which lowers their perceptions of the algorithm's responsibility for the harm, mediates this relationship. Four moderators of this relationship are hypothesized: two algorithm characteristics (whether the algorithm is anthropomorphized and whether it involves machine learning) and two characteristics of the task for which the algorithm is deployed (whether the task is subjective [vs. objective] and whether it is interactive [vs. noninteractive]). The authors find support for the hypotheses in eight experimental studies. The effects of two managerial interventions to manage brand harmcrises caused by algorithm errors are examined. This research advances the literature on brand harm crises, algorithm usage, and algorithmic marketing and generates managerial guidelines to address such crises.
Author Sarial-Abi, Gülen
Srinivasan, Raji
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Keywords algorithm errors
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brand harm crises
theory of mind perception
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Snippet Algorithms, increasingly used by brands, sometimes fail to perform as expected or, even worse, cause harm, leading to brand harm crises. Algorithm failures are...
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SubjectTerms Algorithms
Theory of mind
Subtitle Consumers' Responses to Brand Harm Crises Caused by Algorithm Errors
Title When Algorithms Fail
URI https://www.jstor.org/stable/27114322
https://journals.sagepub.com/doi/full/10.1177/0022242921997082
https://www.proquest.com/docview/2563284609
Volume 85
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