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An Experimental Test of Algorithmic Dismissals

Author

Listed:
  • Brice Corgnet

    (Economic Science Institute, Chapman University)

Abstract

We design a laboratory experiment in which a human or an algorithm decides which of two workers to dismiss. The algorithm automatically dismisses the least productive worker whereas human bosses have full discretion over their decisions. Using performance metrics and questionnaires, we find that fired workers react more negatively to human than to algorithmic decisions in a broad range of tasks. We show that spitefulness exacerbated this negative reaction. Our findings suggest algorithms could help tame negative reactions to dismissals.

Suggested Citation

  • Brice Corgnet, 2023. "An Experimental Test of Algorithmic Dismissals," Working Papers 23-02, Chapman University, Economic Science Institute.
    • Handle: RePEc:chu:wpaper:23-02
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    File URL: https://digitalcommons.chapman.edu/esi_working_papers/382/
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    Citations

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    Cited by:

    1. Mathieu Chevrier & Brice Corgnet & Eric Guerci & Julie Rosaz, 2024. "Algorithm Credulity: Human and Algorithmic Advice in Prediction Experiments," GREDEG Working Papers 2024-03, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France, revised Dec 2024.
    2. Marie-Pierre Dargnies & Rustamdjan Hakimov & Dorothea Kübler, 2026. "Aversion to Hiring Algorithms: Transparency, Gender Profiling, and Self-Confidence," Management Science, INFORMS, vol. 72(1), pages 285-301, January.
    3. Strobel, Christina, 2025. "The impact of process automation on performance," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 117(C).
    4. Mathieu Chevrier & Vincent Teixeira, 2024. "Algorithm Delegation and Responsibility: Shifting Blame to the Programmer?," GREDEG Working Papers 2024-04, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France, revised Sep 2024.
    5. Marie-Pierre Dargnies & Rustamdjan Hakimov & Dorothea Kübler, 2025. "Behavioral Measures Improve AI Hiring: A Field Experiment," Rationality and Competition Discussion Paper Series 532, CRC TRR 190 Rationality and Competition.
    6. Marina Chugunova & Wolfgang J. Luhan, 2025. "Ruled by robots: preference for algorithmic decision makers and perceptions of their choices," Public Choice, Springer, vol. 202(1), pages 1-24, January.

    More about this item

    Keywords

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    JEL classification:

    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D23 - Microeconomics - - Production and Organizations - - - Organizational Behavior; Transaction Costs; Property Rights
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • M50 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - General
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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