Algorithmic Management in Hospitality: Examining Hotel Employees’ Attitudes and Work–Life Balance Under AI-Driven HR Systems

Milena Turčinović, Aleksandra Vujko () and Vuk Mirčetić
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Milena Turčinović: Faculty of Tourism and Hospitality Management, Singidunum University, Danijelova No. 32, 11000 Belgrade, Serbia
Aleksandra Vujko: Faculty of Tourism and Hospitality Management, Singidunum University, Danijelova No. 32, 11000 Belgrade, Serbia
Vuk Mirčetić: Faculty of Applied Management, Economics and Finance in Belgrade, University Business Academy in Novi Sad, Jevrejska 24, 11000 Belgrade, Serbia

Tourism and Hospitality, 2025, vol. 6, issue 4, 1-26

Abstract: This study investigates hotel employees’ perceptions of AI-driven human resource (HR) management systems within the Accor Group’s properties across three major European cities: Paris, Berlin, and Amsterdam. These diverse urban contexts, spanning a broad portfolio of hotel brands from luxury to economy, provide a rich setting for exploring how AI integration affects employee attitudes and work–life balance. A total of 437 employees participated in the survey, offering a robust dataset for structural equation modeling (SEM) analysis. Exploratory factor analysis identified two primary factors shaping perceptions: AI Perceptions, which encompasses employee views on AI’s impact on job performance, communication, recognition, and retention, and balanced management, reflecting attitudes toward fairness, personal consideration, productivity, and skill development in AI-managed environments. The results reveal a complex but optimistic view, where employees acknowledge AI’s potential to enhance operational efficiency and career optimism but also express concerns about flexibility loss and the need for human oversight. The findings underscore the importance of transparent communication, contextual sensitivity, and continuous training in implementing AI systems that support both organizational goals and employee well-being. This study contributes valuable insights to hospitality management by highlighting the relational and ethical dimensions of algorithmic HR systems across varied organizational and cultural settings.

Keywords: algorithmic management; hospitality industry; employee perceptions; work–life balance; AI-driven HR systems (search for similar items in EconPapers)
JEL-codes: Z3 Z30 Z31 Z32 Z33 Z38 (search for similar items in EconPapers)
Date: 2025
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