The DOI matches its Crossref record.
Actionable Knowledge: Design Causality in the Service of Consequential Theory
Abstract
Knowledge produced by empirical research can have external validity, which means it is relevant to the everyday world. Actionable knowledge is that knowledge required to implement the external validity (relevance) in that world. The claim is made that the concept of causality that underlies much rigorous empirical research makes it difficult to transform knowledge with high external validity into actionable knowledge. Moreover, this concept of causality can lead to knowledge that, if made actionable, could inhibit learning and, in some cases, produce undesirable unethical consequences. A different concept of causality is proposed that enhances actionability. Design causality is defined, and how it can be implemented is illustrated.
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Cited by
Big data analytics: transforming data to action
Bumblauskas, D., Nold, H., Bumblauskas, P., & Igou, A. (2017) · Business Process Management Journal · doi:10.1108/bpmj-03-2016-0056 · Cited by 130
Metadata
- Authors
- Argyris, C.
- Venue
- The Journal of Applied Behavioral Science
- Publisher
- SAGE Publications
- Published
- 1996-12
- Volume
- 32
- Issue
- 4
- Pages
- 390-406
- ISSN
- 0021-8863 (ISSN-L)
- 1552-6879
- OpenAlex
- W1982408789
- Cited by
- 261
- References
- 0
- FWCI
- 5.81
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Actionable Knowledge: Design Causality in the Service of Consequential Theory. https://app.cochat.ai/papers/10.1177/0021886396324004
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- Argyris, C. (1996). Actionable Knowledge: Design Causality in the Service of Consequential Theory. The Journal of Applied Behavioral Science. https://doi.org/10.1177/0021886396324004
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.
