Robo-Advising: Algorithm Appreciation

Counter to the widespread conclusion of algorithm aversion, our results suggest that people are willing to rely on algorithmic advice under circumstances that apply to many decisions. They suggest moderators to algorithm aversion and contribute to “theory of machine,” which examines lay beliefs about how algorithmic and human judgment differ.



Citation:

Jennifer Logg, Julia Minson, and Don Moore (2018) ,"Robo-Advising: Algorithm Appreciation", in NA - Advances in Consumer Research Volume 46, eds. Andrew Gershoff, Robert Kozinets, and Tiffany White, Duluth, MN : Association for Consumer Research, Pages: 63-67.

Authors

Jennifer Logg, Harvard Business School, USA
Julia Minson, Harvard Business School, USA
Don Moore, University of California Berkeley, USA



Volume

NA - Advances in Consumer Research Volume 46 | 2018



Share Proceeding

Featured papers

See More

Featured

No Self to Spare: How the Cognitive Structure of the Self Influences Moral Behavior

Rima Touré-Tillery, Northwestern University, USA
Alysson Light, University of the Sciences

Read More

Featured

G10. The Effects of self-construal on evaluations of brand logo colors

Eunmi Jeon, Sungkyunkwan University
Myungwoo Nam, Georgia Tech, USA

Read More

Featured

Donate Today or Give Tomorrow? Adding a Time Delay Increases Donation Amount but not Willingness to Donate

Emily Powell, New York University, USA
Minah Jung, New York University, USA
Joachim Vosgerau, Bocconi University, Italy
Eyal Pe'er, Bar-Ilan University

Read More

Engage with Us

Becoming an Association for Consumer Research member is simple. Membership in ACR is relatively inexpensive, but brings significant benefits to its members.