“They” threaten my work: How AI service robots negatively impact frontline hotel employees through organizational dehumanization

Tao Xu, Yu-Hao Zheng, Jinhua Zhang, Zixuan Wang

Research output: Contribution to journalArticlepeer-review

Abstract

This study aims to investigate the potential effects of AI service robots on frontline employees (FLEs) in the hospitality industry. Drawing on coping theory, we established a theoretical model to study the responses of FLEs when they work alongside service robots, which is represented by the variables of infrastructure capability (IC) and service robot performance (SRP). We considered organizational dehumanization (OD) as a state of stress for FLEs resulting from the presence of service robots. The findings of partial least squares structural equation modelling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) suggest that OD mediates the positive influence of AI service robot adoption on FLEs’ service performance. Simultaneously, the adoption of AI service robots significantly undermines FLE’s service passion through OD’s mediation. This study provides new insights into the mechanisms of human-robot interaction and suggests practical approaches for the hospitality industry.
Original languageEnglish
Article number104162
JournalInternational Journal of Hospitality Management
Volume128
DOIs
Publication statusPublished - 20 Mar 2025

ASJC Scopus subject areas

  • Tourism, Leisure and Hospitality Management
  • Strategy and Management

Keywords

  • AI service robot
  • Frontline employee
  • Frontline employee passion
  • Infrastructure capabilities
  • Organizational dehumanization
  • Service performance

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