Algorithmic Management

Brief description

Exploring the fusion of algorithms with business operations, this research area dives deep into the intricacies of both platform-based and conventional business models. It examines the dynamics of multiple stakeholders on multi-sided platforms, casting a spotlight on the future of work. At its core, the research seeks to uncover the balance between automated decision-making and the pressing need for algorithmic accountability in today's digital age.

Algorithmic Management
Algorithmic Management
  • Algorithmic Control and the Human Element: How does algorithmic control influence the perceptions and experiences of individual workers, especially in gig economies, and what are the implications for their legitimacy and well-being?
  • Algorithmic Management's Janus Face: In what ways does algorithmic management present both opportunities and challenges, and how can organizations navigate the balance between harnessing its potential and mitigating its adverse effects?
  • Technological Stress from Algorithmic Oversight: How does algorithmic control impact the mental well-being and stress levels of workers, in both platform-driven and more traditional work environments, and what strategies can be employed to alleviate such technostress?
  • Platform Governance and Control Dynamics: How do governance structures and controls on online platforms influence stakeholder behaviors, and what are the broader implications of such structures for platform sustainability and growth?
  • Ecosystem Architecture and Network Dynamics: How does the structural flexibility of a digital platform — from closed to open systems — shape its emergent behaviors, user interactions, and long-term viability?
  • DFG: Algorithmic Control: A Legitimacy Perspective on Worker-level Implications AlgoWork
  • DFG: Accountable Artificial Intelligence-based Systems: A Multi-Perspective Analysis Accountable AI
  • ZEVEDI: Verantwortungsbewusste algorithmische Entscheidungsfindung in der Arbeitswelt Projekt
  • ZEVEDI: Digital Governance (tbd)
  • Wiener, M., Cram, W. A., & Benlian, A. (2023). Algorithmic control and gig workers: a legitimacy perspective of Uber drivers. European Journal of Information Systems, 32(3), 485-507
  • Adam, M., Croitor, E., Werner, D., Benlian, A., & Wiener, M. (2023). Input control and its signalling effects for complementors' intention to join digital platforms. Information Systems Journal, 33(3), 437-466
  • Benlian, A., Wiener, M., Cram, W. A., Krasnova, H., Maedche, A., Möhlmann, M., Recker, J., & Remus, U. (2022). Algorithmic Management: Bright and Dark Sides, Practical Implications, and Research Opportunities. Business & Information Systems Engineering, 64(6)
  • Cram, W. A., Wiener, M., Tarafdar, M., & Benlian, A. (2022) “Examining the Impact of Algorithmic Control on Uber Drivers’ Technostress,” Journal of Management Information Systems, 39(2), 426-453
  • Saunders, C., Benlian, A., Henfridsson, O., Wiener, M. (2020): „IS Control and Governance“, Mis Quarterly Research Curations, A. Bush and A. Rai (eds.). http://misq.org/research-curations.
  • Thies, F., Wessel, M., Benlian A. (2018): „Network effects on crowdfunding platforms: Exploring the implications of relaxing input control“, Information Systems Journal, 28 (6), 1239-1262.
  • Wessel, M., Thies, F., Benlian, A. (2017): „Opening the floodgates – The implications of increasing platform openness in crowdfunding“, Journal of Information Technology, 32 (4), 344-360.
  • Thies, F., Wessel, M., Benlian, A. (2016): „Effects of Social Interaction Dynamics on Platforms“, Journal of Management Information Systems, 33 (3), 843-873.
  • Benlian, A.; Hilkert D.; Hess, T. (2015): “How open is this platform? The meaning and measurement of platform openness from the complementors’ perspective”, Journal of Information Technology, 30(3), 209-228.