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Record W2898855336 · doi:10.5539/mas.v12n11p1

The Influence of Knowledge Management Uses on Total Quality Management Practices in Commercial Banks of Jordan

2018· article· en· W2898855336 on OpenAlexvenueno aff
Bader Yousef Obeidat, Lama Hashem, Ra’ed Masa’deh

Bibliographic record

VenueModern Applied Science · 2018
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsKnowledge managementBusinessData managementTotal quality managementQuality (philosophy)Knowledge transferKnowledge acquisitionRegression analysisComputer scienceMarketingData mining

Abstract

fetched live from OpenAlex

This study examines the influence of knowledge management uses on total quality management practices in commercial banks of Jordan.A quantitative research design, using regression analysis was applied in this study and a total of 250 valid returns were obtained through a questionnaire distributed to the employees of commercial banks in Jordan. Knowledge management uses was adopted as an independent variable with four subgroups: knowledge acquisition, knowledge storage, knowledge transfer and knowledge application. Total quality management practices were adopted as dependent variable with five subgroups: top management support, employee's involvement, continuous improvement, customer focus, and data driven decision management.The results show that knowledge management uses significantly affects total quality management practices at three of its dimensions (knowledge acquisition, knowledge storage, and knowledge transfer) but it showed that no effect on knowledge application. The implications of this study are discussed at the end of this paper.

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)0.001
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 score0.939
Threshold uncertainty score0.330

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.033
GPT teacher head0.317
Teacher spread0.284 · 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

Citations8
Published2018
Admission routes1
Has abstractyes

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