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Home | Events Archive | Tensions under Hybrid Supervision: The Role of Human Support in Enhancing Algorithmic Management within Traditional Employment
Seminar

Tensions under Hybrid Supervision: The Role of Human Support in Enhancing Algorithmic Management within Traditional Employment


  • Location
    Vrije Universiteit Amsterdam, HG-09A33
    Amsterdam
  • Date and time

    March 22, 2024
    12:00 - 13:00

This seminar is organized by organized by ABRI and the KIN Center for Digital Innovation. Please find more information and register here.

Abstract

In recent years, the integration of algorithmic management across various sectors has significantly transformed supervisory roles, impacting the dynamics of work environments and worker well-being. While much of the scholarly focus, as seen in studies by Cameron & Rahman (2022) and Mohlmann, Zalmanson, Henfridsson, and Gregory (2021), has been on gig economy workers in platform-based work, the effects of algorithmic management alongside human supervision in more traditional employment settings have received less attention. This study addresses this gap through a two-year qualitative exploration within a unionized smart transportation organization, where daily operations are guided by both an app and human managers. Despite the structured support from employment rights and unionization, the dual management system presents unique challenges for worker experience and well being. Our study identifies key tension sources such as the ability to override algorithmic decisions, conflicting instructions from both management systems, and disparities in performance evaluation criteria, all contributing to operational inefficiencies, emotional strain, and a sense of disconnect between drivers and the company. To mitigate these issues, the study examines the evolving roles of the control room, highlighting effective communication, emotional support, and emergency response mechanisms as critical interventions. By elucidating the complex dynamics and challenges within hybrid managed work settings, this research suggests a refined approach in the design and management of algorithmic systems, underscored by the imperative to foster a psychologically safe and productive working environment.