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Record W2800895200 · doi:10.5539/ass.v14n5p60

The Influences of Justice and Trust on the Organizational Citizenship Behavior of Generation X and Generation Y

2018· article· en· W2800895200 on OpenAlexvenueno aff
Amphaphorn Leelamanothum, Khahan Na-Nan, Sungworn Ngudgratoke

Bibliographic record

VenueAsian Social Science · 2018
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsOrganizational citizenship behaviorEconomic JusticeOrganizational justiceCitizenshipPsychologyStructural equation modelingSocial psychologyOrganizational commitmentPolitical scienceLawComputer science

Abstract

fetched live from OpenAlex

This study aimed to study the influences of justice and trust on the organizational citizenship behavior. The questionnaire respondents were the workers at Rajamangala University of Technology. Data analysis was done through structural equation modeling to test the purpose model and compare between the groups via multiple groups analysis approach. It was found that justice and trust have a positive statistical significant influence on organizational citizenship behavior. Moreover, justice has a positive statistical significant influence on trust. Generation X and Generation Y differently perceive the influences of justice and trust on organizational citizenship behavior. Generation X paid attention to the influence of justice on the organizational citizenship behavior while generation Y paid attention to the influence of trust on justice, the chief will implement justice in the organization for both generations to build trust in the chief and the organization. This would lead to future achievements in the organization.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.877
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.028
GPT teacher head0.264
Teacher spread0.236 · 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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