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Algorithmic Routines and Dynamic Inertia: How Organizations Avoid Adapting to Changes in the Environment
Author(s) -
Omidvar Omid,
Safavi Mehdi,
Glaser Vern L.
Publication year - 2023
Publication title -
journal of management studies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.398
H-Index - 184
eISSN - 1467-6486
pISSN - 0022-2380
DOI - 10.1111/joms.12819
Subject(s) - inertia , phenomenon , compartmentalization (fire protection) , adaptation (eye) , computer science , dynamic capabilities , organizational change , technological change , microfoundations , risk analysis (engineering) , knowledge management , business , economics , artificial intelligence , psychology , public relations , political science , biochemistry , chemistry , physics , classical mechanics , quantum mechanics , macroeconomics , enzyme , neuroscience
Organizations often fail to adequately respond to substantive changes in the environment, despite widespread implementation of algorithmic routines designed to enable dynamic adaptation. We develop a theory to explain this phenomenon based on an inductive, historical case study of the credit rating routine of Moody’s, an organization that failed to adapt to substantial changes in its environment leading up to the 2008 financial crisis. Our analysis of changes to the firm’s algorithmic credit rating routine reveals mechanisms whereby organizations dynamically produce inertia by taking actions that fail to produce significant change. Dynamic inertia occurs through bounded retheorization of the algorithmic model, sedimentation of assumptions about inputs to the algorithmic model, simulation of the unknown future, and specialized compartmentalization. We enable a better understanding of organizational inertia as a socio‐material phenomenon by theorizing how – despite using algorithmic routines to improve organizational agility – organizations dynamically produce inertia, with potentially serious adverse consequences.