MétaCan
Menu
Back to cohort
Record W2884164938 · doi:10.17722/ijme.v11i2.457

Importance of Empowering Leadership, Reward and Trust towards Knowledge Sharing

2018· article· en· W2884164938 on OpenAlexvenueno aff
Muhammad Hanif, M. Farooq, Muhammad Ayaz Khan

Bibliographic record

VenueInternational Journal of Management Excellence · 2018
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessKnowledge managementKnowledge sharingPsychologyPublic relationsComputer sciencePolitical science

Abstract

fetched live from OpenAlex

The aim of study is to explain the impact of empowering leadership, reward and trust on knowledge sharing. Main idea is to identify the relationship between them. Study will motivate the organizations to use knowledge for success, and also will motivate the researchers to give more focus on knowledge sharing for further researches.Outcome of study shows that empowering leadership, reward and trust affect the knowledge sharing positively within the organization, and also plays a major role to motivate the employees, to participate in knowledge sharing freely.  Empowering leadership provides a environment for other members of organization to share their minds with others. Reward gives an opportunity for employees to participate in knowledge sharing and get benefit in shape of reward and as well in shape of knowledge from others. Trust is climate in which employees show their confident on other employees, and trust motivates the employees to share their knowledge with others. Knowledge sharing provides an opportunity to share knowledge and get helpful knowledge from the minds of other humans of organization. The conclusion of this study based on the interpretation of data analysis.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.281
Threshold uncertainty score0.349

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 science0.0010.001
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 head0.038
GPT teacher head0.289
Teacher spread0.250 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Management ExcellenceSame topicOrganizational and Employee PerformanceFrench-language works237,207