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Record W2021723934 · doi:10.5539/ass.v11n12p11

Organizational Citizenship Behavior and Bank Profitability: Examining relationships in an Iranian Bank

2015· article· en· W2021723934 on OpenAlexvenueno aff
Khaled Nawaser, Moein Ahmadi, Yousef Ahmadi, Maliheh Dorostkar

Bibliographic record

VenueAsian Social Science · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Leadership and Management Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsProfitability indexOrganizational citizenship behaviorCitizenshipBusinessOrder (exchange)Pearson product-moment correlation coefficientPolitical scienceOrganizational commitmentFinancePublic relationsMathematicsStatisticsLaw

Abstract

fetched live from OpenAlex

Organizational citizenship behavior is an individual and voluntary behavior that is not designed directly by formal reward system. Nevertheless, it causes increase in effectiveness and efficiency of organization performance. This study aims to evaluate and analyze relationship between organization citizenship behavior and profitability of branches of Mellat Bank in Kerman Province. Sample consists of all formal employees of Mellat Bank branches in Kerman Province that work in 87 branches of Kerman Province. In order to collect required data, a questionnaire was used for variable ' organizational citizenship behavior' and for evaluation of bank profitability, records and documents of bank branches were used. Results of Pearson correlation coefficient suggest that there is a significant relationship between citizenship behavior and profitability in branches of Mellat Bank in Kerman Province. Based on results from regression analysis, it was revealed that dimensions of civil participation and respect predict profitability of the bank branches positively and significantly. Keywords: organizational citizenship behavior, profitability, Mellat Bank

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)0.001
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 score0.336
Threshold uncertainty score0.603

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0010.002
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 head0.090
GPT teacher head0.277
Teacher spread0.187 · 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

Citations5
Published2015
Admission routes1
Has abstractyes

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