W4223898259 Peer-reviewed research AI × management and organizations

Algorithmic Routines and Dynamic Inertia: How Organizations Avoid Adapting to Changes in the Environment

Omid Omidvar · Mehdi Safavi · Vern L. Glaser

Also recorded as: doi:10.1111/joms.12819

Journal of Management Studies · 2022-05-05

Recorded claims
1
coded from the inspected source
Evidence classes
1
crossref-api-metadata
Recorded limitations
2
stated, never hidden

From the hash-bound evidence releases

Recorded claims

Each claim states what the inspected source says, at the recorded location—bounded by its scope and graded by its confidence. Nothing here is a synthesis across works.

The abstract explains how algorithmic credit-rating routines can reproduce organizational inertia through bounded model revision, sedimented inputs, simulation, and specialization.

confidence: high crossref-api-metadata apw-c1-obot-journals

Scope: abstract-level

Structured relationships

In-corpus citations

Only source-supplied cites relationships whose two endpoints are admitted are shown. Invocation evidence remains a separate relationship.

Boundaries

Limitations & independence

Recorded at coding time, carried with the work forever. A claim without its limits is not evidence.

Recorded limitations

  • Crossref metadata only; full text was not inspected.
  • The publisher surface was not queried after the lane’s quarantined dynamic-challenge response; no independent publisher-page verification was attempted.

Source independence

publisher-only