The DOI matches its Crossref record; 65 of the 66 references it cites were found in a registry or an index.
A Dynamic Theory of Organizational Knowledge Creation
Abstract
This paper proposes a paradigm for managing the dynamic aspects of organizational knowledge creating processes. Its central theme is that organizational knowledge is created through a continuous dialogue between tacit and explicit knowledge. The nature of this dialogue is examined and four patterns of interaction involving tacit and explicit knowledge are identified. It is argued that while new knowledge is developed by individuals, organizations play a critical role in articulating and amplifying that knowledge. A theoretical framework is developed which provides an analytical perspective on the constituent dimensions of knowledge creation. This framework is then applied in two operational models for facilitating the dynamic creation of appropriate organizational knowledge.
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In the citing paper
“We propose that the SECI model of knowledge creation (Nonaka and Takeuchi 1995) provides empirically testable design principles for AI agent memory architecture.”
From From Organizational Knowledge to AI Agent Memory: Empirical Validation of the SECI Model on the LongMemEval Benchmark (2026) · cites this paper as Nonaka 1994
In the citing paper
“Nonaka and Takeuchi (1995) proposed that organizational knowledge is created through a continuous spiral of four conversion modes.”
From From Organizational Knowledge to AI Agent Memory: Empirical Validation of the SECI Model on the LongMemEval Benchmark (2026) · cites this paper as Nonaka 1994
In the citing paper
“The organizational knowledge creation theory proposes that the new knowledge is created through processes of tacit and explicit conversion: socialization, externalization, combination, and internalization (Erden, Von Krogh, & Nonaka, 2008;Nonaka, Toyama, & Konno, 2000;Nonaka, 1994).”
From Linking knowledge management, organizational learning and memory (2020) · cites this paper as Nonaka, 1994
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“…view has reached growing interest in both information technology and systems, strategic management, innovation management and organizational literature (Nonaka, 1994; Spender, 1996; Nonaka and Takeuchi, 1995; Alavi and Leidner, 2001; Soto-Acosta and Merono-Cerdan, 2008; Bresciani, 2010).”
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Method
Metadata
- Authors
- Nonaka, I.
- Affiliations
- Hitotsubashi University (JP)
- Corresponding author
- Nonaka, Ikujiro
- ORCID
- Nonaka, Ikujiro
- Venue
- Organization Science
- Published
- 1994-02
- Volume
- 5
- Issue
- 1
- Pages
- 14-37
- ISSN
- 1047-7039 (ISSN-L)
- 1526-5455
- OpenAlex
- W2132454116
- Cited by
- 17,809
- References
- 66
- Citations by year
- 2026: 506 · 2025: 438 · 2024: 460 · 2023: 529 · 2022: 717 · 2021: 722 · 2020: 732 · 2019: 776 · 2018: 777 · 2017: 820 · 2016: 706 · 2015: 887 · 2014: 922 · 2013: 1016 · 2012: 944
- FWCI
- 409.35
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Organization Science (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Knowledge Management and Sharing
- Social Sciences › Business, Management and Accounting › Strategy and Management › Innovation and Knowledge Management
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Organizational Learning and Leadership
- Keywords
- organizational knowledge creation, tacit knowledge, explicit knowledge, knowledge creation process, knowledge management, knowledge articulation
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 ›
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