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Record W2101646438 · doi:10.5267/j.msl.2013.02.022

A study on the effect of human resource management on financial performance: A case study of Bank Melli Esfahan using Harvard method

2013· article· en· W2101646438 on OpenAlexvenueno aff
Mashallah Valikhani Dehaghani, Mohsen Rahimi Semiromi, Mohamad Malekmohamadi Faradonbeh

Bibliographic record

VenueManagement Science Letters · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting and Organizational Management
Canadian institutionsnot available
Fundersnot available
KeywordsHuman resourcesBusinessComputer scienceManagementEconomics

Abstract

fetched live from OpenAlex

This paper presents an empirical investigation to study the relationship between human resource management and financial performance of some Iranian banks.The proposed study of this paper designs a questionnaire and distributes it among all management teams who work in city of Esfahan, Iran.Three questionnaires have been designed, which are associated with human resources, present financial performance and desirable financial performance with 22 questions.Cronbach alpha has been calculated as 0.86, which is well above the minimum desirable limit of 0.70.The study uses Pearson correlation ratio as well as regression technique and structural equation modeling to examine five hypotheses associated with this survey and the results of our all investigations have confirmed that there are some positive and meaningful relationship between human resources development and financial figures.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.018
GPT teacher head0.261
Teacher spread0.242 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations1
Published2013
Admission routes1
Has abstractyes

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