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Record W4394975964 · doi:10.1002/kpm.1777

Analyzing the effects of knowledge management on organizational performance through knowledge utilization and sustainability

2024· article· en· W4394975964 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 and Process Management · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Capital and Performance Analysis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsKnowledge managementOrganizational learningBusinessSustainabilityComputer science

Abstract

fetched live from OpenAlex

Abstract In today's turbulent business environment, gaining sustainable competitive advantage requires organizations to manage knowledge capabilities effectively and use resources efficiently. The primary objective of this study is to explore the relationship among knowledge management (KM) processes, including knowledge generation, knowledge codification, and knowledge sharing, with knowledge utilization, sustainability, and organizational performance. The research mainly examines both the direct effect of KM on organizational performance and its indirect effect through sustainability and knowledge utilization. A theoretical framework is introduced and tested using data gathered from companies within the services sector in Kuwait. The results indicate that knowledge utilization and sustainability fully mediate the relationship between KM and organizational performance. Both knowledge utilization and sustainability exert direct and positive effects on organizational performance while being directly influenced by KM. Accordingly, it is suggested that the firms enhance their performance by effectively managing knowledge capabilities appropriately, utilizing knowledge, and investing in sustainability and organizational resources.

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)0.000
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: none
Teacher disagreement score0.691
Threshold uncertainty score0.906

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.012
GPT teacher head0.261
Teacher spread0.249 · 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