MétaCan
Menu
Back to cohort
Record W3120094447 · doi:10.5430/ijfr.v12n3p78

The Determinants of Islamic and Conventional Banks Profitability in the GCC Region

2021· article· en· W3120094447 on OpenAlexvenueno aff
Bassam Jaara, Mohammad Aldahiyat, Ismail AL-Takryty

Bibliographic record

VenueInternational Journal of Financial Research · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsnot available
Fundersnot available
KeywordsProfitability indexIslamBusinessReturn on assetsPanel dataProxy (statistics)Monetary economicsBivariate analysisFinancial systemGross domestic productEconomicsFinanceEconometricsMacroeconomicsMathematicsStatistics

Abstract

fetched live from OpenAlex

The purpose of this study is to examine the factors affecting the profitability levels of commercial banks whether Islamic and non-Islamic over the period 2000-2018, to suggest ways to enhance the Islamic and non-Islamic banks profitability levels’ in the GCC countries. This research employed Bivariate analysis and panel regression in the investigation process. The study employed return on assets ratio as a proxy for banks profitability. The study found out that conventional banks are more efficient than Islamic banks in terms of profitability levels. There are substantial variances between both Islamic and conventional banks in terms of the determinants of banks' profitability. It is found that 89% of the Islamic bank’s profitability and 85% of conventional banks profitability influenced by bank size, market to book value, capital ratio, cash to assets, gross domestic product GDP, GDP growth, and inflation.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

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 communication0.0010.000
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 head0.054
GPT teacher head0.355
Teacher spread0.301 · 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 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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Financial ResearchSame topicIslamic Finance and Banking StudiesFrench-language works237,207