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Record W2037882382 · doi:10.5430/jms.v5n1p73

Knowledge Management and Organizational Learning from the Employee Perspectives: A Study from Saudi Arabia Context

2014· article· en· W2037882382 on OpenAlex
Wageeh A. Nafei

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 Management and Strategy · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsnot available
Fundersnot available
KeywordsCompetitive advantageKnowledge managementContext (archaeology)BusinessPerspective (graphical)Set (abstract data type)USableData collectionMarketingDescriptive researchHuman resource managementPsychologySociologyGeographyComputer scienceSocial science

Abstract

fetched live from OpenAlex

This paper investigates the relationship between Knowledge Management (KM) and Organizational Learning (OL) from the employee perspective.KM has emerged as one of the most important areas in management practices and established as a basic resource for firms and economies. KM is an area of research and practice that is still searching for a stable set of core concepts and practical applications. OL is considered to be one of the most important issues in modern managerial literature. Also, OL is one of the most important organizational factors that can direct the behavior and attitudes of the employees in the organizations. This study was conducted at Saudi banks in Al-Taif Governorate. It is practical, according to its purpose, and descriptive according to its data collection method. The present study investigates the evaluative attitudes of the employees towards KM and OL. It will also illustrate the relationship between KM and OL. Two groups of employees were examined. Of the 350 questionnaires that were distributed, 285 usable questionnaires were returned, a response rate of 81%.The finding reveals that there are differences among the employees regarding their evaluative attitudes towards KM and OL. Also, this study reveals that there is a statistically significant relationship between KM and OL. Accordingly, the study provided a set of recommendations including the necessity to pay more attention to KM and OL. This will achieve its success currently and in the future, besides attaining a competitive advantage.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.317
Threshold uncertainty score0.557

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.031
GPT teacher head0.282
Teacher spread0.251 · 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