Insights Into the Black Box: Input Explainability of Algorithmic Decisions Drives Consumer Satisfaction in the Digital World

We find that the negative effects of algorithmic (vs. human) choice on satisfaction are driven by lower trust in the algorithm, which results from people’s perception that the algorithm is a black box, i.e., is less transparent. We reveal explainability as an effective intervention to increase satisfaction with algorithmic choice.



Citation:

Ipek Demirdag and Suzanne Shu (2020) ,"Insights Into the Black Box: Input Explainability of Algorithmic Decisions Drives Consumer Satisfaction in the Digital World", in NA - Advances in Consumer Research Volume 48, eds. Jennifer Argo, Tina M. Lowrey, and Hope Jensen Schau, Duluth, MN : Association for Consumer Research, Pages: 297-298.

Authors

Ipek Demirdag, University of California Los Angeles, USA
Suzanne Shu, University of California Los Angeles, USA



Volume

NA - Advances in Consumer Research Volume 48 | 2020



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