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Organizations as Algorithms: A New Metaphor for Advancing Management Theory

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  • Vern L. Glaser
  • Jennifer Sloan
  • Joel Gehman

Abstract

According to the ‘Point’ essay, management research's reliance on corporate data threatens to replace objective theory with profit‐biased ‘corporate empiricism’, undermining the scientific and ethical integrity of the field. In this ‘Counterpoint’ essay, we offer a more expansive understanding of big data and algorithmic processing and, by extension, see promising applications to management theory. Specifically, we propose a novel management metaphor: organizations as algorithms. This metaphor offers three insights for developing innovative, relevant, and grounded organization theory. First, agency is distributed in assemblages rather than being solely attributed to individuals, algorithms, or data. Second, machine‐readability serves as the immutable and mobile base for organizing and decision‐making. Third, prompting and programming transform the role of professional expertise and organizational relationships with technologies. Contrary to the ‘Point’ essay, we see no theoretical ‘end’ in sight; the organization as algorithm metaphor enables scholars to build innovative theories that account for the intricacies of algorithmic decision‐making.

Suggested Citation

  • Vern L. Glaser & Jennifer Sloan & Joel Gehman, 2024. "Organizations as Algorithms: A New Metaphor for Advancing Management Theory," Journal of Management Studies, Wiley Blackwell, vol. 61(6), pages 2748-2769, September.
    • Handle: RePEc:bla:jomstd:v:61:y:2024:i:6:p:2748-2769
    DOI: 10.1111/joms.13033
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    References listed on IDEAS

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    1. Omid Omidvar & Mehdi Safavi & Vern L. Glaser, 2023. "Algorithmic Routines and Dynamic Inertia: How Organizations Avoid Adapting to Changes in the Environment," Journal of Management Studies, Wiley Blackwell, vol. 60(2), pages 313-345, March.
    2. Stella Pachidi & Hans Berends & Samer Faraj & Marleen Huysman, 2021. "Make Way for the Algorithms: Symbolic Actions and Change in a Regime of Knowing," Organization Science, INFORMS, vol. 32(1), pages 18-41, January.
    3. Taylor, Frederick Winslow, 1911. "The Principles of Scientific Management," History of Economic Thought Books, McMaster University Archive for the History of Economic Thought, number taylor1911.
    4. Poon, Martha, 2009. "From new deal institutions to capital markets: Commercial consumer risk scores and the making of subprime mortgage finance," Accounting, Organizations and Society, Elsevier, vol. 34(5), pages 654-674, July.
    5. Kirsten Martin, 2019. "Ethical Implications and Accountability of Algorithms," Journal of Business Ethics, Springer, vol. 160(4), pages 835-850, December.
    6. Davenport, Thomas H., 2018. "The AI Advantage: How to Put the Artificial Intelligence Revolution to Work," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262039176, December.
    7. David Beer & Roger Burrows, 2007. "Sociology and, of and in Web 2.0: Some Initial Considerations," Sociological Research Online, , vol. 12(5), pages 67-79, September.
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    Cited by:

    1. Retkowsky, Jana & Hafermalz, Ella & Huysman, Marleen, 2024. "Managing a ChatGPT-empowered workforce: Understanding its affordances and side effects," Business Horizons, Elsevier, vol. 67(5), pages 511-523.

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