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
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.
Integrity signals
Registry
Cites
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.
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
A Theory of Cognitive Dissonance
Festinger, L. (1957) · doi:10.1515/9781503620766 · Cited by 24,241
Organizational Learning: A Theory of Action Perspective
Argyris, C., & Schön, D. A. (1997) · Reis · doi:10.2307/40183951 · Cited by 11,113
Organizational learning: The contributing processes and the literatures
Huber, G. P. (1991) · Organization Science · doi:10.1287/orsc.2.1.88 · Cited by 8,072
Bounded rationality and organizational learning
Simon, H. A. (1991) · Organization Science · doi:10.1287/orsc.2.1.125 · Cited by 3,028
Individual learning and organizational routine: Emerging connections
Cohen, M. D. (1991) · Organization Science · doi:10.1287/orsc.2.1.135 · Cited by 384
Cited by
An organizational learning framework: From intuition to institution
Crossan, M. M., Lane, H. W., & White, R. E. (1999) · The Academy of Management Review · doi:10.2307/259140 · Cited by 4,544
Self-citationSiguaw, J. A., Simpson, P. M., & Enz, C. A. (2006) · Journal of Product Innovation Management · doi:10.1111/j.1540-5885.2006.00224.x · Cited by 544
오석영 (2013) · The Korean Journal of Human Resource Development Quarterly · doi:10.18211/kjhrdq.2013.15.4.005 · Cited by 4
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
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.