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Record W3194107358 · doi:10.33844/ijol.2021.60528

Linking Self-efficacy and Organizational Citizenship Behavior: A Moderated Mediation Model

2021· article· en· W3194107358 on OpenAlexaff
Saif Ullah, Basharat Raza, Wasif Ali, Sana Amjad

Bibliographic record

VenueInternational Journal of Organizational Leadership · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsOrganizational citizenship behaviorMediationPsychologyModerated mediationSocial psychologyCitizenshipOrganizational commitmentPolitical science

Abstract

fetched live from OpenAlex

This study investigates the relationship between self-efficacy and Organization Citizenship Behavior (OCB), moderated by incivility and mediated by pro-social motivation. Self-efficacy is the employee's belief in him about his skills to perform tasks in different situations. The direct and indirect effects of self-efficacy of teachers towards their OCB through prosocial motivation have been observed in this study. For this purpose, data has been collected through questionnaires (N = 301) using convenience sampling in three-time phases with two weeks gaps between each phase. SPSS 22.0 and Amos 22.0 were used along with Process by Hayes for moderated mediation analysis. The results indicate that self-efficacy leads to organizational citizenship behavior (OCB) and pro-social motivation, moderated by incivility and mediated by pro-social motivation. In a nutshell, this study demonstrates self-efficacy enhances pro-social motivation and OCB within academic settings with reference to Pakistan, advocating that if teachers are confident to perform a task, they can also demonstrate their extra-role behavior. The present study contributes to the literature by analyzing the novel framework within the Pakistan context. The mediating effect of prosocial motivation between teachers’ self-efficacy and OCB has not been discussed in the prior studies. The implications, discussion, and conclusion are also discussed.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.226
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.043
GPT teacher head0.258
Teacher spread0.215 · 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
Published2021
Admission routes1
Has abstractyes

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