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Record W3143406348 · doi:10.33736/ijbs.3160.2021

Organizational Citizenship Behaviour and the Mediating Role of Organizational Commitment: A Study of Private Universities

2021· article· en· W3143406348 on OpenAlexaff
Sofiah Kadar Khan, Mumtaz Ali Memon, Alex Cheing, Hiram Ting

Bibliographic record

VenueInternational Journal of Business and Society · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsBriercrest College and Seminary
Fundersnot available
KeywordsOrganizational citizenship behaviorOrganizational commitmentTransformational leadershipOrganizational behavior and human resourcesOrganizational justiceOrganizational learningStructural equation modelingLatent variablePsychologyOrganizational engineeringOrganizational cultureOrganizational effectivenessOrganization developmentSocial psychologyOrganizational studiesPartial least squares regressionPublic relationsPolitical scienceManagementEconomicsMathematics

Abstract

fetched live from OpenAlex

This study aims to perpetuate the investigation of organizational commitment and its mediating role as it is one of the most crucial components in understanding organizational behaviour. A total of 324 samples were collected from the academics of 20 private universities in Malaysia. Partial Least Squares Structural Equation Modelling (PLS-SEM) using SmartPLS3.0 was used to perform the latent variable analysis. The results indicate transformational leadership, organizational culture, and organizational justice are the significant predictors of organizational commitment, and organizational commitment, in turn, is found to be a strong predictor of organizational citizenship behaviour. Moreover, the results of mediating analysis highlight that organizational commitment significantly mediates the hypothesized relationship. The implications of the findings are discussed and recommendations for future research are proposed.

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 score0.081
Threshold uncertainty score0.303

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 communication0.0000.000
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 head0.009
GPT teacher head0.218
Teacher spread0.209 · 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

Citations11
Published2021
Admission routes1
Has abstractyes

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