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Record W4383068936 · doi:10.3390/su151310501

Board Gender Diversity and Banks Profitability for Business Viability: Evidence from Serbia

2023· article· en· W4383068936 on OpenAlexaff
Stefan Milojević, Marko Milašinović, Aleksandra Mitrović, Jasmina Ognjanović, Jelena Raičević, Nebojša Zdravković, Snežana Knežević, Malči Grivec

Bibliographic record

VenueSustainability · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsWorkplace Health, Safety and Compensation Commission
Fundersnot available
KeywordsProfitability indexCorporate governanceBusinessReturn on assetsPanel dataAccountingReturn on equityGender diversityEquity (law)PandemicSample (material)Coronavirus disease 2019 (COVID-19)FinanceEconomicsPolitical scienceMedicine

Abstract

fetched live from OpenAlex

As an important topic in the field of corporate governance, the influence of the board of directors’ characteristics on the profitability of corporations is examined here. This paper examines the influence of the board of directors’ and chief executive officers’ (CEO) characteristics on the profitability of banks in Serbia. In this study, the characteristics of boards of directors were examined in terms of size and the participation of women, and the characteristics of CEOs were examined similarly in terms of women’s participation. The research was conducted on a sample of 23 commercial banks from Serbia in the period from 2017 to 2021. Profitability was measured by the rate of return on operating assets (ROA) and the rate of return on equity (ROE). The results of the panel regression analysis indicate that the size of the board of directors had a positive impact on bank profitability during the COVID-19 pandemic period, while this impact was not statistically significant before the pandemic. The participation of women on the board of directors did not have a statistically significant impact on bank profitability before or during the COVID-19 pandemic. It has been found that the participation of women as CEOs had a negative impact on bank profitability before and during the COVID-19 pandemic.

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)0.006
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.156
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.001
Scholarly communication0.0000.001
Open science0.0010.002
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 head0.155
GPT teacher head0.339
Teacher spread0.184 · 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

Citations8
Published2023
Admission routes1
Has abstractyes

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