Algorithmic Management and Workplace Bullying: The Relevance of Specific Employee Experiences Across Work Environments

Abstract

Algorithmic management (AM) is regarded as a crucial advancement in current workplaces. AM has the potential to alter job tasks and reorganize entire work processes, thus affecting the working conditions of employees. Nonetheless, research on the possible consequences for workplace relationships remains limited. This study narrows this gap by investigating the association between AM and perceived workplace bullying by supervisors or co-workers. Based on multilevel analyses of a sample of 4929 employees in 160 workplaces derived from German linked employer–employee data, specific experiences with AM contribute more to perceptions of workplace bullying than the mere frequency of involvement. Negative experiences such as reduced control and design options, violation of privacy and constant monitoring, are associated with the perception of bullying. Shared experiences of employees within workplaces are additionally important in explaining bullying. The findings suggest a nondeterministic nature of AM, with variations in its implementation across different work environments.