Algorithmic management and decision-making
Track 4
Track chairs
Armin Alizadeh
TU Darmstadt
Monideepa Tarafdar
University of Massachusetts Amherst
Ulrich Remus
University of Innsbruck
Track description
Digital technologies are rapidly changing how organisations manage work. Algorithms increasingly augment managerial decision-making by assisting or collaborating with their human counterparts (Leavitt et al., 2025; Tarafdar et al., 2023), but they also automate managerial processes entirely by directly coordinating and controlling workers (Möhlmann et al., 2021; Kellogg et al., 2020). Algorithmic decision-making and management can offer substantial benefits to organisations, enabling efficient scaling of business models and operations (Benlian et al., 2022). For example, in platform-based companies such as Uber, intelligent algorithms take on the role of human managers by selecting and replacing workers as needed, assigning tasks, and providing detailed feedback on daily work behavior (Möhlmann et al., 2021). But algorithmic decision-making and management are now also commonplace in traditional organisational contexts. A global OECD survey of 6,047 firms found that 74% already use at least one algorithmic management tool to instruct, monitor, or evaluate their employees (Milanez et al., 2025). Yet, by algorithmically determining who receives tasks, who advances, and ultimately who can participate in the organization at all, algorithmic management does not merely make management more efficient; it draws new digital borders within and around organizations, shaping access, opportunity, and the voice of those being algorithmically managed.
This track focuses on the implications of algorithmic decision-making and management for organisations, workers, managers, and how these actors make sense of, respond to, and cope with increasingly automated management systems (Lippert et al., 2026; Weber et al., 2025). We invite submissions that examine how algorithmic management reconfigures existing agency and power structures (Hillebrand et al., 2025; Wood 2024), how it leads to hybrid control configurations (Hao et al., 2026), how human managers navigate their coexistence with algorithmic counterparts (Jarrahi et al., 2021), and how workers retain agency and voice within algorithmically managed organisations (Hsieh et al., 2025). We also welcome contributions that address the ethical design of algorithmic management systems and related policymaking (Gal et al., 2020; Spiekermann et al., 2022). Finally, we invite research on how algorithmic management and its organisational embedding (Alizadeh et al., 2025) affect worker well-being (Tarafdar et al., 2023), and how workers push back through algoactivistic practices (Jiang et al., 2021).
We welcome contributions from all theoretical and methodological perspectives, drawing on IS, management, and neighboring disciplines, and addressing individual, organisational, and societal levels of analysis.
Topics of interest
- What are the novel features and affordances of algorithmic management systems, and how can their key dimensions be conceptualised across different work contexts?
- How do emerging technological developments (such as generative agentic AI) impact our conceptual understanding of algorithmic management?
Algorithmic management and digital borders
- How does algorithmic management reconfigure power and social structures (such as the worker-manager and worker-worker relationships), and what new forms of inclusion and exclusion does it produce?
- What technical, organisational, and governance measures are needed to ensure that algorithmic management systems foster rather than undermine meaningful connectivity within organisations?
- How can participatory approaches to algorithmic management bridge tensions between workers, managers, and the systems that mediate their relationships?
Design of algorithmic management systems
- How do organisations design, deploy, and adapt algorithmic management systems, and how can workers be meaningfully involved in these processes?
- What ethical principles should guide the development and use of algorithmic management systems, and how can organisations and policymakers effectively govern them?
Organisational implications of algorithmic management
- What are the enabling and inhibiting factors for the adoption and use of algorithmic management systems?
- How can (traditional) organisations decide on the ‘right’ division of labor between human and algorithmic managers?
- In what ways do algorithmic systems serve as “organisational memory,” and how does this affect issues of accountability and transparency?
Managerial implications of algorithmic management
- What new roles and competencies emerge for human managers coexisting with algorithmic counterparts?
- What skills do managers need to effectively navigate algorithmically managed environments?
Worker-level implications of algorithmic management
- How does algorithmic management shape group dynamics, team cohesion, and collective identity among workers?
- What are the effects of algorithmic management on worker performance, well-being, and agency?
- Under what conditions do algorithmic management systems empower workers (e.g., by enabling self-management, voice, or collective bargaining)?
Associate editors
Adam, Martin
University of Göttingen, Germany
Armin Alizadeh
TU Darmstadt (Germany)
Azka Umair
University of Galway, Ireland
Benlian, Alexander
TU Darmstadt, Germany
Chen, Liwei
University of Cincinnati, USA
Cram, W. Alec
University of Waterloo, Canada
De Lima Salge, Carolina Alves
University of Georgia, USA
Giermindl, Lisa Marie
Zurich University of Applied Sciences, Switzerland
Hao, Hui
University of Memphis, USA
Hödl, Tatjana
University of Bern, Switzerland
Jabagi, Nura
Université Laval, Canada
Klöpper, Miriam
Norwegian University of Science and Technology, Norway
Molinaro, Bastian
LMU Munich, Germany
Monideepa Tarafdar
University of Massachusetts Amherst (USA)
Moritz, Josephine
University of Münster, Germany
Nguyen, Long The
Washington State University, USA
Taylor, Joseph
California State University, Sacramento, USA
Ulrich Remus
University of Innsbruck (Austria)
Van den Hooff, Bart
Vrije Universiteit Amsterdam, Netherlands
Weber, Matthias
University of Innsbruck, Austria
Wiener, Martin
TU Dresden, Germany
Zalmanson, Lior
Tel Aviv University, Israel
