When Guests Abuse Service Robots: Employees’ Intervention and Retaliation Intentions

Service robots in hospitality face increasing abuse, yet employee responses to such incidents remain underexamined. Using an experimental design approach, this study explores how abuse type (verbal vs. physical) and perpetrator type (child vs. adult) jointly affect intervention and retaliation intentions of employees. The results revealed that verbal abuse by children elicited stronger intervention and retaliation intentions in hospitality employees, with their sympathy toward the robot mediating this effect. This study contributes to deontic justice theory by extending its application from human victims to non-human agents (e.g., service robots), and by demonstrating that justice-related responses are jointly shaped by both the severity of the abusive act and the social identity of the perpetrator. Practically, this research yields practical guidance for hospitality workplaces on service robot abuse incidents, including training employees to work alongside service robots, the design of robot responses, and organizational policy.

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Publication Details

Journal
Cornell Hospitality Quarterly
Published
2026-10-26
DOI
https://doi.org/10.1177/19389655261496888
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

When Guests Abuse Service Robots: Employees’ Intervention and Retaliation Intentions

Shi Tracy Xu, Zhiwei Lin, Hongbo Liu, Erin Chao Ling
Cornell Hospitality Quarterly
AI in Service Interactions
article

When Guests Abuse Service Robots: Employees’ Intervention and Retaliation Intentions

Shi Tracy Xu, Zhiwei Lin, Hongbo Liu, Erin Chao Ling
article en

Abstract

Service robots in hospitality face increasing abuse, yet employee responses to such incidents remain underexamined. Using an experimental design approach, this study explores how abuse type (verbal vs. physical) and perpetrator type (child vs. adult) jointly affect intervention and retaliation intentions of employees. The results revealed that verbal abuse by children elicited stronger intervention and retaliation intentions in hospitality employees, with their sympathy toward the robot mediating this effect. This study contributes to deontic justice theory by extending its application from human victims to non-human agents (e.g., service robots), and by demonstrating that justice-related responses are jointly shaped by both the severity of the abusive act and the social identity of the perpetrator. Practically, this research yields practical guidance for hospitality workplaces on service robot abuse incidents, including training employees to work alongside service robots, the design of robot responses, and organizational policy.

Cornell Hospitality Quarterly
Sun Yat-sen University (CN), Chinese University of Hong Kong (HK), University of Surrey (GB)
Openalex Percentile: Top 13%
AI in Service Interactions
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