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Working with artificial intelligence surveillance during the COVID-19 pandemic: a mixed investigation of the influence mechanism on job engagement in hospitality industry

Author

Listed:
  • Hairong Zhao
  • Junbang Lan
  • Ting Lyu
  • Guojun Zeng

Abstract

This paper examines the interaction effects of social support (supervisor support and coworker support) and AI surveillance on employee job engagement drawing on the social exchange theory. Mixed research methods were applied. Researchers collected 358 valid time-lagged designed questionnaires and tested the model using a path analysis approach. The results revealed that there is a moderated mediation mechanism in relationships between supervisor support/coworker support and job engagement, in which both self-efficacy and self-esteem are mediating variables and AI surveillance plays a moderating role. Specifically, when the degree of job control with AI surveillance is at a low level, the effect of supervisor support/coworker support on employees’ self-efficacy/self-esteem is stronger. The indirect relationship between supervisor support/coworker support and job engagement through self-esteem is moderated by job control with AI surveillance as well, and the indirect relationship becomes stronger when job control with AI surveillance is lower. Findings from a series of semi-structured post-hoc interviews with 18 hotel employees interpretatively support the survey results. This research fills this gap by analyzing relationships among social support, AI surveillance, and job engagement and provides positive suggestions for hotel operation and employee management with AI surveillance during pandemic.

Suggested Citation

  • Hairong Zhao & Junbang Lan & Ting Lyu & Guojun Zeng, 2023. "Working with artificial intelligence surveillance during the COVID-19 pandemic: a mixed investigation of the influence mechanism on job engagement in hospitality industry," Current Issues in Tourism, Taylor & Francis Journals, vol. 26(20), pages 3318-3335, October.
  • Handle: RePEc:taf:rcitxx:v:26:y:2023:i:20:p:3318-3335
    DOI: 10.1080/13683500.2022.2117593
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