W7160295950 Peer-reviewed research AI × management and organizations

Backfiring AI? AI Deployment in Workplace

Di Yuan · Manmohan Aseri · Narayan Ramasubbu

Also recorded as: doi:10.1287/mnsc.2023.03108

Management Science · 2026-05-04

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.

A game-theoretic model of a competitive workplace shows how AI-enabled transfer of high performers' knowledge can weaken their incentives; the modeled payoff from deployment depends on workforce heterogeneity, skill composition, skill disparity, compensation policy, and AI efficacy.

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

Scope: publisher-deposited abstract metadata; workplace and firm-performance mechanism

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

  • Abstract-level Crossref metadata only; the publisher landing page could not be retained because public retrieval was access-blocked.
  • Full text was not inspected.

Source independence

publisher-only