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
H11. Not for Me: Identity Needs and Consumer Interest in Different Types of Co-creation
Lagnajita Chatterjee, University of Illinois at Chicago, USA
David Gal, University of Illinois at Chicago, USA
Featured
Psychological Reactions to Human Versus Robotic Job Replacement
Armin Granulo, Technical University of Munich
Christopher Fuchs, Technical University of Munich
Stefano Puntoni, Erasmus University Rotterdam, The Netherlands
Featured
K12. Use language to change people’s mind: The persuasive power of online marketing communications
Xun He, Katholieke University Leuven, Belgium
Barbara Briers, Vlerick Business School
Luk Warlop, Norwegian School of Management, Norway