Algorithm Attraction Versus Aversion: the Role of the Perceived Self-Efficacy of the Decision Maker
Nowadays algorithms are used to generate recommendations in numerous areas, including ones that are pure matter of taste. Across four studies, we demonstrate that consumers value the same recommendation differently depending on the framing of its source—an algorithm versus human expert—and their own perceived level of self-efficacy.
Citation:
Gizem Yalcin, Anne-Kathrin Klesse, and Darren Dahl (2018) ,"Algorithm Attraction Versus Aversion: the Role of the Perceived Self-Efficacy of the Decision Maker", in NA - Advances in Consumer Research Volume 46, eds. Andrew Gershoff, Robert Kozinets, and Tiffany White, Duluth, MN : Association for Consumer Research, Pages: 935-935.
Authors
Gizem Yalcin, Erasmus University Rotterdam, The Netherlands
Anne-Kathrin Klesse, Erasmus University Rotterdam, The Netherlands
Darren Dahl, University of British Columbia, Canada
Volume
NA - Advances in Consumer Research Volume 46 | 2018
Share Proceeding
Featured papers
See MoreFeatured
The Impact of Product Type on Disposal Intentions
MUSTAFA KARATAŞ, Koc University, Turkey
Rabia BAYER, Koc University, Turkey
Zeynep GURHAN-CANLI, Koc University, Turkey
Featured
The Viciousness and Caring of Sharing: Conflicts and Motivations of Online Shamers
Chen Pundak, Tel Aviv University, Israel
Yael Steinhart, Tel Aviv University, Israel
Jacob Goldenberg, IDC
Featured
Accounting For Gains From Discounted Credit
Andong Cheng, University of Delaware, USA
Ernest Baskin, Yale University, USA