Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/59136
Title: Bon Appetit! Robot Persuasion for Food Recommendation
Contributor(s): Herse, Sarita (author); Vitale, Jonathan  (author)orcid ; Ebrahimian, Daniel (author); Tonkin, Meg (author); Ojha, Suman (author); Sidra, Sidra (author); Johnston, Benjamin (author); Phillips, Sophie (author); Gudi, Siva Leela Krishna Chand (author); Clark, Jesse (author); Judge, William (author); Williams, Mary-Anne (author)
Publication Date: 2018
DOI: 10.1145/3173386.3177028
Handle Link: https://hdl.handle.net/1959.11/59136
Abstract: 

The integration of social robots within service industries requires social robots to be persuasive. We conducted a vignette experiment to investigate the persuasiveness of a human, robot, and an information kiosk when offering consumers a restaurant recommendation. We found that embodiment type significantly affects the persuasiveness of the agent, but only when using a specific recommendation sentence. These preliminary results suggest that human-like features of an agent may serve to boost persuasion in recommendation systems. However, the extent of the effect is determined by the nature of the given recommendation.

Publication Type: Conference Publication
Conference Details: HRI 2018: ACM/IEEE International Conference on Human-Robot Interaction, United States of America, 5th to 8th of March, 2018
Source of Publication: ACM/IEEE International Conference on Human-Robot Interaction, p. 125-126
Publisher: Association for Computing Machinery
Place of Publication: United States of America
Fields of Research (FoR) 2020: 4601 Applied computing
Peer Reviewed: Yes
HERDC Category Description: E1 Refereed Scholarly Conference Publication
Appears in Collections:Conference Publication
School of Science and Technology

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