The DOI matches its Crossref record; 102 of the 102 references it cites were found in a registry or an index.
Vicarious Learning, Undersampling of Failure, and the Myths of Management
Abstract
Organizations learn from other organizations. However, the observations available to them are typically a biased sample. The organizations that can be observed at any point in time are the survivors of a selective process that has eliminated a large fraction of the underlying population. In addition, there is a strong tendency to focus on successful organizations in books and the business press. As a result, the available sample of organizations usually undersamples failure. This paper shows that such undersampling of failure can contribute to a variety of false beliefs about effective management. Simply by observing existing organizations, laymen may get a misleading picture of the determinants of corporate performance. In particular, risky practices, even if they are unrelated to performance in the full population of organizations, may seem to be positively related to performance in a sample of survivors. I argue that this bias frequently implies that the organizational theories of managers and other observers of organizations will be systematically biased. Observations of existing organizations will show that unreliable, uninformed practices and practices that involve concentrated resource allocation are superior to reliable, informed practices or practices that involve diversified resource allocation. I show that this implies that observations of existing organizations will produce compelling but potentially misleading evidence for the significance several common managerial practices.
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Cites
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Cited by
Liang, H., Saraf, N., Hu, Q., & Xue, Y. (2007) · MIS Quarterly · doi:10.2307/25148781 · Cited by 3,921
Ambidexterity as a dynamic capability: Resolving the innovator's dilemma
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Everyone's an influencer: quantifying influence on twitter
Bakshy, E., Hofman, J. M., Mason, W. A., & Watts, D. J. (2011) · Proceedings of the fourth ACM international conference on Web search and data mining · doi:10.1145/1935826.1935845 · Cited by 1,689
Linnenluecke, M. K., Griffiths, A., & Winn, M. (2012) · Business Strategy and the Environment · doi:10.1002/bse.708 · Cited by 457
Dutta, D. K., & Crossan, M. M. (2005) · Entrepreneurship Theory and Practice · doi:10.1111/j.1540-6520.2005.00092.x · Cited by 451
Metadata
- Authors
- Denrell, J.
- Venue
- Organization Science
- Published
- 2003-06
- Volume
- 14
- Issue
- 3
- Pages
- 227-243
- ISSN
- 1047-7039 (ISSN-L)
- 1526-5455
- OpenAlex
- W208491018
- Cited by
- 520
- References
- 102
- FWCI
- 21.74
- Type
- journal article
- Language
- en
- Open access
- closed
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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.