W4408794157 Peer-reviewed research AI × management and organizations

Human-Algorithm Collaboration with Private Information: Naïve Advice-Weighting Behavior and Mitigation

Maya Balakrishnan · Kris Johnson Ferreira · Jordan Tong

Also recorded as: doi:10.1287/mnsc.2022.03850

Management Science · 2025-03-24

Recorded claims
1
coded from the inspected source
Evidence classes
1
journal-toc-listing
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 publisher preview examines how human decision makers use and adjust algorithmic recommendations when they hold private information unavailable to the algorithm.

confidence: high journal-toc-listing apw-c1-obot-journals

Scope: publisher TOC preview abstract

Structured relationships

In-corpus citations

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

Cites (0)

No in-corpus outgoing citation is available in the current enrichment coverage.

Cited by (0)

No in-corpus incoming citation is available in the current enrichment coverage.

Boundaries

Limitations & independence

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

Recorded limitations

  • Publisher TOC preview abstract is truncated; full text was not inspected.
  • Special-issue membership is established by the issue heading.

Source independence

publisher-only