Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 469

The DOI matches its Crossref record; 92 of the 92 references it cites were found in a registry or an index.

Unpacking Prior Experience: How Career History Affects Job Performance

Dokko, Gina, Wilk, Steffanie L., Rothbard, Nancy P.·2009·Organization Science

Abstract

As individuals change jobs more frequently, it is increasingly important to understand what they carry from their prior work experience that affects their performance in a new organizational context. So far, explanations about the imperfect portability of experience have primarily been about firm specificity of knowledge and skill. We draw on psychological theory to propose additional sociocognitive factors that interfere with the transfer of knowledge and skill acquired from prior related work experience. As we hypothesized, we find that task-relevant knowledge and skill mediates the relationship between prior related experience and job performance and that it acts as suppressing mediator of a negative direct relationship between prior related experience and current job performance. We also find that the positive effect of prior related experience on task-relevant knowledge and skill is attenuated by higher levels of experience within the current firm.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1287/orsc.1080.0357

Cites

92 of 92 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 92 references

Cited by

See all 469

Metadata

Authors
Dokko, G., Wilk, S. L., & Rothbard, N. P.
Venue
Organization Science
Published
2009-02
Volume
20
Issue
1
Pages
51-68
ISSN
  • 1047-7039 (ISSN-L)
  • 1526-5455
OpenAlex
W2158932382
Cited by
469
References
92
FWCI
17.58
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Unpacking Prior Experience: How Career History Affects Job Performance. https://app.cochat.ai/papers/10.1287/orsc.1080.0357
The paper
Dokko, G., Wilk, S. L., & Rothbard, N. P. (2009). Unpacking Prior Experience: How Career History Affects Job Performance. Organization Science. https://doi.org/10.1287/orsc.1080.0357

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.