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Assessing Turnover Intentions of Algorithmically Managed Hospitality Workers

In: Information and Communication Technologies in Tourism 2023

Author

Listed:
  • Mónica Segovia-Perez

    (University of Rey Juan Carlos)

  • Brana Jianu

    (University of Surrey)

  • Iis Tussyadiah

    (University of Surrey)

Abstract

Employee turnover has been one of the main concerns facing the hospitality industry. This issue seems to be aggravated in artificial intelligence (AI) environment, where AI implementation is associated with pressure, job alienation, and labor replacement, increasing workers’ desire to quit their job. To analyze the relationship between AI awareness, job alienation, discrimination, and turnover intention, an online survey was distributed to hospitality employees (n = 450). From a series of independent-samples T-tests and regression analyses, this study found employees’ turnover intentions are significantly associated with employees’ concerns of being replaced by AI, perception of job alienation, and workplace discrimination. Importantly, current algorithmically managed workers tend to feel more powerless and discriminated against, and thus have higher turnover intentions. Recommendations for practice and future research are provided.

Suggested Citation

  • Mónica Segovia-Perez & Brana Jianu & Iis Tussyadiah, 2023. "Assessing Turnover Intentions of Algorithmically Managed Hospitality Workers," Springer Proceedings in Business and Economics, in: Berta Ferrer-Rosell & David Massimo & Katerina Berezina (ed.), Information and Communication Technologies in Tourism 2023, pages 349-354, Springer.
    • Handle: RePEc:spr:prbchp:978-3-031-25752-0_39
    DOI: 10.1007/978-3-031-25752-0_39
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