Purpose As algorithmic management (AM) is increasingly implemented in traditional hospitality workplaces, understanding its impact on employees becomes essential. This study aims to investigate how employees’ perceptions of AM influence their resistance to it, well-being and turnover intentions. Design/methodology/approach A mixed-methods approach, combining qualitative interviews (Study 1), quantitative survey (Study 2) and a between-subjects online experiment (Study 3) was used to explore these dynamics under varying conditions of algorithmic control, managerial involvement and algorithmic opacity. Findings The results indicate that while algorithmic enhancements positively influence well-being, they do not diminish resistance to AM, which is primarily driven by algorithmic restraints. Resistance negatively impacts well-being, which in turn drives turnover intentions. A non-linear relationship between enhancements and restraints emerged, indicating an optimal point at which enhancements are maximised. Practical implications Organisations should maintain a moderate level of restraints to optimise perceived enhancements, while actively addressing the emotional and relational impacts of AM. Sustaining managerial involvement and exercising caution with transparency are essential, as excessive openness may increase employee resistance. The proposed Algorithmic Management Impact model provides a foundation for future research across sectors adopting AI, especially where emotional labour and employee agency are central. Originality/value This study identifies resistance as a mediator of employee well-being, and the results indicate that technology acceptance and resistance can coexist. It provides an employee-centred perspective on attitudes towards technology in hospitality, thus offering a novel view compared to prevailing consumer-focused technology acceptance models.
Jianu et al. (2025) studied this question.