Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 362

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

ORGANIZATIONAL LEARNING: DIMENSIONS FOR A THEORY

Crossan, Mary M., Lane, Henry W., White, Roderick E., Djurfeldt, Lisa·1995·The International Journal of Organizational Analysis

Abstract

Organizational learning (OL) is receiving increasing attention from researchers and practitioners alike. In fact, some have suggested that the only sustainable competitive advantage is a firm's ability to learn faster than its competitors. In spite of OL's promise, the field has been slow to evolve. The primary impediments to the development of OL theory are that inconsistent terminology is used for comparable concepts and that different definitions are used to describe the phenomenon. Furthermore, many theorists have neglected to make explicit their underlying assumptions about the phenomenon. Employing an inductive approach, this review surfaces the implicit and explicit assumptions of OL researchers, identifying three key dimensions that differentiate perspectives: (1) unit of analysis—individual, group, organizational, and inter organizational; (2) cognitive/behavioral emphasis; and (3) the learning‐performance relationship.

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 · 10.1108/eb028835

Cites

5 of 5 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 5 references

Cited by

See all 362

Metadata

Authors
Crossan, M. M., Lane, H. W., White, R. E., & Djurfeldt, L.
Venue
The International Journal of Organizational Analysis
Publisher
Emerald
Published
1995-04-01
Volume
3
Issue
4
Pages
337-360
ISSN
1055-3185 (ISSN-L)
OpenAlex
W1982437751
Cited by
362
References
5
FWCI
2.78
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: ORGANIZATIONAL LEARNING: DIMENSIONS FOR A THEORY. https://app.cochat.ai/papers/10.1108/eb028835
The paper
Crossan, M. M., Lane, H. W., White, R. E., & Djurfeldt, L. (1995). ORGANIZATIONAL LEARNING: DIMENSIONS FOR A THEORY. The International Journal of Organizational Analysis. https://doi.org/10.1108/eb028835

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.