MétaCan
Menu
Back to cohort
Record W2913382401 · doi:10.5539/ibr.v12n2p181

The Increase of Organizational Citizenship Behaviour (OCB) Through Islamic Work Ethics, Affective Commitment, and Organizational Identity

2019· article· en· W2913382401 on OpenAlexvenueno aff
Wuryanti Kuncoro, Gunadi Wibowo

Bibliographic record

VenueInternational Business Research · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsOrganizational citizenship behaviorWork ethicPsychologyOrganizational commitmentIslamStructural equation modelingSocial psychologyProductivityWork (physics)Business administrationBusinessTheologyMathematicsEngineering

Abstract

fetched live from OpenAlex

An employee who is willing to voluntarily help fellow co-workers to do work outside the assigned job description and the assistance provided is not included in the performance assessment, can be defined as organizational citizenship behavior (OCB). Podsakoff et.al (2000) states that OCB can influence organizational effectiveness because it can help improve co-workers productivity, increase managerial productivity and streamline the use of organizational resources for productive purposes. This research was conducted to identify the effect of Islamic work ethics, affective commitment and organizational identity on OCB. The data were collected from 110 employees at the Muhammadiyah Islamic Hospital of Kendal and the Muhammadiyah Darul Istiqomah Hospital of Kendal. The data were later analyzed using Structural Equation Modeling (SEM) using the Analysis of Moment Structure (AMOS 24) software. The result indicates that affective commitment and organizational identity have a significant effect on OCB while Islamic work ethics have no significant effect on OCB. The researcher hopes that this research can be developed in future research by adding other variables related to OCB that may have a greater influence on OCB.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.044
GPT teacher head0.343
Teacher spread0.299 · 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.

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

Citations13
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueInternational Business ResearchSame topicJob Satisfaction and Organizational BehaviorFrench-language works237,207