This thesis, entitled " Algorithmic control in hospitality workplaces: the impact on

workplace experience and employee affective well-being", aims to provide a comprehensive

understanding of forms, mechanisms and reactions to algorithmic management, specifically to

algorithmic control in the hospitality sector. The four interrelated studies evaluate existing

knowledge, investigate user perspectives, develop measurement instruments and construct and

validate a model of resistance to algorithmic management and its individual and organisational

outcomes in hospitality workplaces.

Study One formulates the concept of algorithmic normative control by drawing on the

established management literature on labour process and the emerging discourse on algorithmic

management and presents the ‘7Ps’ of algorithmic normative control within a multi-level

process framework that shows how algorithms gradually deconstruct human agency,

reconfigure behaviours, and internalise control through persuasion, pressure, and perception

structuration.

By applying Sociomateriality Theory, Study Two examines the compensatory roles of

managers and algorithmic systems through "enabling control" mechanisms in humanising

algorithmic management. This study contributes to the sociomaterial discourse on algorithmic

management by proposing a theoretical framework for humanised systems in hospitality,

addressing power asymmetries through selective visibility of controls, and distributed agency.

Study Three employs a mixed-methods approach to conceptualise and test the three

dimensional Resistance to Algorithmic Management (RAM) scale and to investigate its

relationship with employee affective well-being in hospitality workplaces. Following a four

stage development process, a 12-item BIRAM scale is developed, which includes affective,

cognitive, and behavioural resistance dimensions.

Study Four engages in a mixed-methods approach to test how enhancements and

restraints of algorithmic management influence resistance, affective well-being, and turnover

intentions of hospitality employees. Testing the model in varying algorithmic control

mechanism, manager’s involvement, and algorithmic opacity conditions, this study finds that

while enhancements positively contribute to affective well-being of employees, they do not

mitigate resistance, which is primarily driven by restraints. Resistance negatively impacts

affective well-being, which subsequently drives turnover intention. Findings further reveal a non-linear relationship between enhancements and restraints, identifying an ‘optimal cost’

point where the perception of enhancements by the employees is maximised.

In sum, this thesis advances knowledge on algorithmic management in the context of

hospitality, by examining forms of control, mechanisms of control, and the multifaceted

impacts on hospitality employees.