Assessing Turnover Intentions of Algorithmically Managed Hospitality Workers

Mónica Segovia-Perez (), Brana Jianu () and Iis Tussyadiah ()
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Mónica Segovia-Perez: University of Rey Juan Carlos
Brana Jianu: University of Surrey
Iis Tussyadiah: University of Surrey

A chapter in Information and Communication Technologies in Tourism 2023, 2023, pp 349-354 from Springer

Abstract: 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.

Keywords: Algorithmic management; Turnover intentions; AI awareness (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-031-25752-0_39

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DOI: 10.1007/978-3-031-25752-0_39

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