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Record W2961448545 · doi:10.1108/jkm-01-2018-0007

Knowledge sabotage as an extreme form of counterproductive knowledge behavior: conceptualization, typology, and empirical demonstration

2019· article· en· W2961448545 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Knowledge Management · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTypologyOriginalityConceptualizationPublic relationsCritical Incident TechniqueBusinessValue (mathematics)Interpersonal communicationKnowledge managementQuality (philosophy)PsychologySociologySocial psychologyMarketingPolitical scienceComputer scienceCreativityEpistemology

Abstract

fetched live from OpenAlex

Purpose This paper introduces the concept of knowledge sabotage as an extreme form of counterproductive knowledge behavior, presents its typology, and empirically demonstrates its existence in the contemporary organization. Design/methodology/approach Through the application of the critical incident technique, this study analyzes 177 knowledge sabotage incidents when employees intentionally provided others with wrong knowledge or deliberately concealed critical knowledge while clearly realizing others’ need for this knowledge and others’ ability to apply it to important work-related tasks. Findings Over 40% of employees engaged in knowledge sabotage, and many did so repeatedly. Knowledge saboteurs usually acted against their fellow co-workers, and one-half of all incidents were caused by interpersonal issues resulting from the target’s hostile behavior, failure to provide assistance to others, and poor performance. Knowledge sabotage was often expressed in the form of revenge against a particular individual, who, as a result, may have been reprimanded, humiliated or terminated. Knowledge saboteurs rarely regretted their behavior, which further confirmed the maliciousness of their intentions. Practical implications Even though knowledge saboteurs only rarely acted against their organizations purposely, approximately one-half of all incidents produced negative, unintentional consequences to their organizations, such as time waste, failed or delayed projects, lost clients, unnecessary expenses, hiring costs, products being out-of-stock, understaffing, or poor quality of products or services. Organizations should develop comprehensive knowledge sabotage prevention policies. The best way to reduce knowledge sabotage is to improve inter-personal relationships among employees and to foster a friendly and collaborative environment. Originality/value This is the first well-documented attempt to understand the phenomenon of knowledge sabotage.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.613
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.058
GPT teacher head0.375
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it