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Record W4361222038 · doi:10.1080/14778238.2023.2193347

Organizational enablers and outcomes of IT affordance actualisation: a socio-technical perspective on knowledge sharing

2023· article· en· W4361222038 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

VenueKnowledge Management Research & Practice · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsAffordanceKnowledge sharingKnowledge managementPerspective (graphical)BusinessGovernment (linguistics)PsychologyComputer science

Abstract

fetched live from OpenAlex

Using the IT affordance lens, this study presents a holistic socio-technical view of the organisational factors that affect the knowledge-sharing (KS) behaviour of employees. It develops and empirically validates a conceptual model that theorises the relationships between KS affordances, organisational culture, management support, and peer KS in order to specify how these relationships shape the KS behaviour of employees. Data for this study was collected using a survey of a large pool of public service employees working at various government agencies (n = 4,090 respondents). The results of this study provide evidence that KS affordances offered by both traditional KS information systems and by enterprise social media increase employees’ overall willingness to share their knowledge. However, these results also show that KS affordances are more likely to be perceived when organisational culture favours KS, and that management support moderates the relationship between KS affordances and employees’ KS behaviour.

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)0.010
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.898
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.128
GPT teacher head0.458
Teacher spread0.331 · 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