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Record W4395066008 · doi:10.62477/jkmp.v24i1.204

Innovation Capability and Sustainable Performance Through Knowledge Management in Small and Medium-sized Enterprises

2024· article· en· W4395066008 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Knowledge Management and Practice · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Capital and Performance Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsIntellectual capitalBusinessKnowledge managementVietnameseQuestionnaireSocial capitalSurvey data collectionCapital (architecture)MarketingComputer scienceFinance

Abstract

fetched live from OpenAlex

Knowledge management (KM) across organizations is based on the realization that integrating knowledge or more broadly intellectual capital (IC) both inside and outside the enterprise helps enhance the innovation capability (INC) and sustainable performance (SUP) of enterprises. The purpose of this study is to examine the effects of internal intellectual capital (IIC), external intellectual capital (EIC), and social capital (SOC) on INC and SUP through KM in SMEs. The survey questionnaire was sent to managers working in Vietnamese SMEs. SPSS and AMOS software were used for data analysis. The results indicate that IIC, EIC, and SOC have positive impacts on the INC and SUP of SMEs through KM activities. These findings hope to be useful for scholars and especially SME owners to understand more thoroughly the relationships between IC, SOC, and KM, as well as the influence of these relationships on INC and SUP, while providing new insight and useful suggestions for owners of SMEs in acquiring and exploiting knowledge from outside to fill knowledge gaps within the enterprise.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.920
Threshold uncertainty score0.823

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.004
Open science0.0000.001
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 head0.025
GPT teacher head0.281
Teacher spread0.255 · 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