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Record W4402461096 · doi:10.5539/jel.v13n6p144

Knowledge Sharing: A Key Success Factor for Organization’s Performance

2024· article· en· W4402461096 on OpenAlexvenueno aff
Chula Chareonvong, Nathaphon Noyaime, Phra Thanawut Sanakulchai, Phra Jamlong Pilaphan, Pongsatean Luengalongkot, Wanchai Dhammasaccakarn, Lertlak Jaroensombut, Thongphon Promsaka Na Sakolnakorn, Akkakorn Chaiyapong

Bibliographic record

VenueJournal of Education and Learning · 2024
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsKey (lock)Factor (programming language)PsychologyKnowledge managementComputer scienceComputer security

Abstract

fetched live from OpenAlex

Organizational management is very important in running an efficient business and keeping up with the modern era. The purpose of this article is to present organizational problems, challenges, and key successes factor for an organization’s performance. The first phase of the paper presents the problems seen in organizations, such as corporate culture, employees in understaffed, and inadequate support. In addition, it presents the seven steps of the organizational development process. Finally, this paper presents the key success factors for an organization’s performance: the importance of change agent leadership; improved efficiency; a focus on customer value, managing an organization with expertise, and using smart management, technology. In addition, change management is a management method that leads to the reformation of organizational management strategies, including planning and various work systems of the organization that are linked to all changes; thus, every change has consequences. Therefore, change management is used to manage change in a positive way and minimize its impact.

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.

How this classification was reachedexpand

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.453
Threshold uncertainty score0.310

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.020
GPT teacher head0.288
Teacher spread0.268 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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